|
Palabras clave |
|
search window in the upper left-w hand corner of the screen includes a record of one's past searches, a Key Word In Context (
|
KWIC) |
concordance of the results (with SGML tags visible), and -- in the column headed "Components" -- a list of the categories that are marked with SGML tags |
window in the upper left-w hand corner of the screen includes a record of one's past searches, a Key Word In Context (KWIC)
|
concordance |
of the results (with SGML tags visible), and -- in the column headed "Components" -- a list of the categories that are marked with SGML tags and |
printed text into computer-readable forms or produce digitized images, CD-ROM drives, large color monitors, and text-analysis software that can generate indices, collations,
|
concordances, |
word-lists, statistical analyses, and hypertexts. Image-viewing software allows one to work with color and grayscale digital images alongside the searchable databases. Figure 2 |
Resources Lyrics and Music Archives Spoken Corpus WebGrep for NSEC94 -- A 100KB spoken corpus consisting of a 90-minute conversation by Americans. You can retrieve
|
KWIC |
lines by entering a keyword. A service provided by Masatoshi Sugiura (Nagoya University) Online Condordancing Kwic On AltaVista -- by Sato Hiroaki WebGrep for NSEC9 4 |
a 90-minute conversation by Americans. You can retrieve KWIC lines by entering a keyword. A service provided by Masatoshi Sugiura (Nagoya University) Online Condordancing
|
Kwic |
On AltaVista -- by Sato Hiroaki WebGrep for NSEC9 4 contains 90-minute dialogue (100KB) of two Americans. You can retrieve lin es by entering a |
project by Masatoshi Sugiura (Nagoya University). Public Domain Modern English Search from the University of Michigan Concordances of Great Books -- Fully Searchable Word Indexes AltaVista
|
KWIC |
-- Sato Hiroaki English Phrase Collection -- Menu in Japanese Back to: CEJL Home Page |
can retrieve lin es by entering a keyword. A project by Masatoshi Sugiura (Nagoya University). Public Domain Modern English Search from the University of Michigan
|
Concordances |
of Great Books -- Fully Searchable Word Indexes AltaVista KWIC -- Sato Hiroaki English Phrase Collection -- Menu in Japanese Back to: CEJL Home Page |
|
KWIC |
KWIC The Perl script below (adapted from Dan Malamed's 2kwic.pl) will produce kwic concordances on a match, but a) will not detect multiple |
KWIC
|
KWIC |
The Perl script below (adapted from Dan Malamed's 2kwic.pl) will produce kwic concordances on a match, but a) will not detect multiple occurrencences |
KWIC KWIC The Perl script below (adapted from Dan Malamed's 2kwic.pl) will produce
|
kwic |
concordances on a match, but a) will not detect multiple occurrencences on a line, b) nor find complex patterns across several lines. Can someone suggest |
a) will not detect multiple occurrencences on a line, b) nor find complex patterns across several lines. Can someone suggest other ways of writing simple
|
kwic |
programs in Perl? Should I split into an array, use Perl's format, etc? All suggestions are welcome. Christer Geisler, post-graduate fellow #---------------------------------------------------- #!/usr/bin/ |
Perl's format, etc? All suggestions are welcome. Christer Geisler, post-graduate fellow #---------------------------------------------------- #!/usr/bin/perl # #check for correct usage if ($#ARGV < 2) { print "usage:
|
kwic |
<filename1> \t\t<string1> \t\t<max. total output width>\n"; exit; }; open(F, $ARGV[0]) || die "Couldn't open $ARGV[0]: $!\n"; shift; $str1 |
KWIC KWIC The Perl script below (adapted from Dan Malamed's 2kwic.pl) will produce kwic
|
concordances |
on a match, but a) will not detect multiple occurrencences on a line, b) nor find complex patterns across several lines. Can someone suggest other |
Speech Recognition Corpus FFMTIMIT: Acoustic-Phonetic Continuous Speech Corpus Far Field Microphone Recordings Parallel Text Corpora English French Bilingual Hansard WHO and Hansard Shareware Announcements
|
KWIC/ |
Concordance Tools Corpus Wizrad for Win16/Win32 (KWIC) from NED30616@pcvan.or.jp MonoConc for Windows (Concordance) from Michael Barlow Japanese Concordance (for Windows): info |
Corpus Far Field Microphone Recordings Parallel Text Corpora English French Bilingual Hansard WHO and Hansard Shareware Announcements KWIC/Concordance Tools Corpus Wizrad for Win16/Win32 (
|
KWIC) |
from NED30616@pcvan.or.jp MonoConc for Windows (Concordance) from Michael Barlow Japanese Concordance (for Windows): info in [ Big5 (with ETen Kana Chars) | ISO-2022- |
Recognition Corpus FFMTIMIT: Acoustic-Phonetic Continuous Speech Corpus Far Field Microphone Recordings Parallel Text Corpora English French Bilingual Hansard WHO and Hansard Shareware Announcements KWIC/
|
Concordance |
Tools Corpus Wizrad for Win16/Win32 (KWIC) from NED30616@pcvan.or.jp MonoConc for Windows (Concordance) from Michael Barlow Japanese Concordance (for Windows): info in |
French Bilingual Hansard WHO and Hansard Shareware Announcements KWIC/Concordance Tools Corpus Wizrad for Win16/Win32 (KWIC) from NED30616@pcvan.or.jp MonoConc for Windows (
|
Concordance) |
from Michael Barlow Japanese Concordance (for Windows): info in [ Big5 (with ETen Kana Chars) | ISO-2022-JP ] from Takashi Dictionaries List of Dictionaries WordNet Home |
Hansard Shareware Announcements KWIC/Concordance Tools Corpus Wizrad for Win16/Win32 (KWIC) from NED30616@pcvan.or.jp MonoConc for Windows (Concordance) from Michael Barlow Japanese
|
Concordance |
(for Windows): info in [ Big5 (with ETen Kana Chars) | ISO-2022-JP ] from Takashi Dictionaries List of Dictionaries WordNet Home Page and Databases (Cognitive Science |
Work Head-Word and Rhyme-Word Concordances to His Poetry by Clifton Hall, Samuel Coleman (Hardcover - January 1995) Special Order Our Price: $140.00 15.
|
Kwic |
Concordance to John Cleland's Memoirs of a Woman of Pleasure (Garland Reference Library of the Humanities, Vol 829) by Samuel S. Coleman, Michael J. |
and the Structure of Society by James Samuel, Coleman Out of Print--Try our out-of-print search service! 8. Head-Word and Rhyme-Word
|
Concordances |
to Des Minnesangs Fruhling : A Complete Reference Work by Clifton D. Hall, Samuel Coleman (Hardcover - September 1997) Special Order Our Price: $140.00 9. The |
Coleman Out of Print--Try our out-of-print search service! 14. Walther Von Der Vogelweide : A Complete Reference Work Head-Word and Rhyme-Word
|
Concordances |
to His Poetry by Clifton Hall, Samuel Coleman (Hardcover - January 1995) Special Order Our Price: $140.00 15. Kwic Concordance to John Cleland's Memoirs |
Head-Word and Rhyme-Word Concordances to His Poetry by Clifton Hall, Samuel Coleman (Hardcover - January 1995) Special Order Our Price: $140.00 15. Kwic
|
Concordance |
to John Cleland's Memoirs of a Woman of Pleasure (Garland Reference Library of the Humanities, Vol 829) by Samuel S. Coleman, Michael J. Preston |
and Thomas Paine. Complete works of Robert G. Ingersoll. True Seeker - will allow you to search the Bahá'í writings using a KeyWord In Context (
|
KWIC) |
search. World Scripture - comparative anthology of themes in sacred texts by Dr. Andrew Wilson. Copyright © 2001 Yahoo! Inc. - Company Information - Suggest a Site - FAQ |
religion. Bahá'í Academics Resource Library - extensive collection of Bahá'í texts. Bahá'í Writings - works of The Báb, Bahá'u'lláh, and other authors.
|
Concordances |
of Scriptures - full text and word search for the Bible, Apocrypha, Koran, Bhagavad-Gita, Tao Te Chung, and others. Internet Sacred Text Archive - archive of |
of a word. In many fields of study such a list is called a concordance. It is also similar to a key word in context (
|
kwic) |
index, except that the index does not have to be restricted to particular words. [Software: 18 files, 603 kB] Open 384 English vocabulary Antworth, Evan; |
third file. [Software: 1 file, 18 kB] Open 308 XRef 0.1b Prepares both a copy of a text file with line numbers, and a
|
concordance |
list of words in the file. [Software: 1 file, 9 kB] Open 309 Evolutions A utility program that will convert series of spaces in a |
a short section of the context preceding and following each occurrence of a word. In many fields of study such a list is called a
|
concordance. |
It is also similar to a key word in context (kwic) index, except that the index does not have to be restricted to particular words. |
of fragments appearing in Stephens/Winkler but not used in earlier volumes. The completion of this critical project, added thus to the mechanical TLG microfiche
|
KWIC |
Concordance to the Greek Novelists and to indices or lexica already existing for some texts (A.T., Long., Xen. Eph.) adds considerably to our capacity |
GCN) Hansen, Harder, Aerts, Carver. Hock, R., Perkins, J., edd., Ancient Fiction and Early Christian Literature, Scholars Press, Society of Biblical Literature, due Spring 1998.
|
CONCORDANCE |
Beta, S., De Carli, E., Zanetto, G. edd., Lessico dei romanzieri greci IV , Hildesheim/ Zürich/NY 1997. Takes account, in an Appendix, of fragments appearing |
fragments appearing in Stephens/Winkler but not used in earlier volumes. The completion of this critical project, added thus to the mechanical TLG microfiche KWIC
|
Concordance |
to the Greek Novelists and to indices or lexica already existing for some texts (A.T., Long., Xen. Eph.) adds considerably to our capacity to |
in the AB, IN, INC, INO, PA, PAC, PAO, PST, and TI fields. Highlighting must be on during SEARCH in order to use the HIT,
|
KWIC, |
and OCC display formats. Format | Content | Examples --------|----------------------------------------------|-------------- AB |Abstract |D AB, TI AG |Agent |D AG AGN |Agent Number |D AG AGN AI (1) |Application |
ICS, |D STPC | ICA, ICI, NCL, CC, TI | TRIAL |TI plus Index Data |D TRIAL HIT |Fields containing highlighted hit terms |D HIT 1-5
|
KWIC |
|Highlighted hit terms plus 20 words on either |D 1-7 TI KWIC | side (KeyWord-In-Context) | OCC |Number of occurrences of hit terms and |
D TRIAL HIT |Fields containing highlighted hit terms |D HIT 1-5 KWIC |Highlighted hit terms plus 20 words on either |D 1-7 TI
|
KWIC |
| side (KeyWord-In-Context) | OCC |Number of occurrences of hit terms and fields |D OCC | in which they occur | (1) By default, patent numbers, application |
04/ICA |ICA IPC, Index (complementary) |/ICI |S C07D205:08/ICI |ICI IPC, Main (current (IPC6) with |/ICM |S B21B001-00/ICM |IC, ICM (511)
|
concordance |
to previous | | | editions) | | | IPC, Main Old (511) |/ICMO |S B60B011-02/ICMO |IC, ICMO IPC, Secondary (current) (512) |/ICS |S C01B003-12/ICS |IC, ICS |
ICMO |IC, ICMO IPC, Secondary (current) (512) |/ICS |S C01B003-12/ICS |IC, ICS IPC, Secondary Old (with |/ICSO |S H01J023-36/ICSO |IC, ICSO
|
concordance |
(512)) | | | Inventor (72) (3) (current |/IN |S SCHULTE/IN |IN, INC, INO and old) | (or /AU)|S HAUSKE, JAMES/IN | Inventor Address (current) (3) |/INA |
IC | (ICM, ICMO, ICS, ICSO, ICA, ICI) | ICA |IPC, Additional (Supplementary) |D ICA ICI |IPC, Index (Complementary) |D ICI ICM |IPC, Main (current (IPC4) with
|
concordance |
|D ICM | to previous editions) | ICMO |IPC, Main Old |D ICMO ICS |IPS, Secondary (current) |D ICS ICSM |IPC, Secondary Old (with concordance) |D ICSM |
IPC4) with concordance |D ICM | to previous editions) | ICMO |IPC, Main Old |D ICMO ICS |IPS, Secondary (current) |D ICS ICSM |IPC, Secondary Old (with
|
concordance) |
|D ICSM IN |Inventor (includes INC, INO) |D IN INC |Inventor Current |D INC INO |Inventor Old |D INO INS |Inventor Standard |D INS LA |
allows for more direct access to a particular subcorpus. You can retrieve information about a corpus with getName(), getSize(), getDesc(), getLabel() and similar functions get
|
KWIC |
lines for a certain corpus position with getKwic(), or an extended context with getContext() retrieve frequency information of a word in that particular corpus with |
with addCorpus(), addCorpora(), getAvailableCorpora(), setActive() and others retrieval of overall frequency counts with getFreq() for a word and getSize() for the corpus size retrieval of
|
concordance |
lines via query() Each instance of Cue has its own working set, and you can have multiple instances of it active at any one time. |
method (by way of an Enumeration). It describes a single instance of a word in the data, and you can use it to retrieve a
|
concordance |
line of this item with getKwic() look at the context with getContext() get a word relative to it with getWord() Stand-alone Classes There are |
way to illustrate how to use an API. Here are some code snippets that show how to use CUE in order to implement a simple
|
concordancer: |
import java.util.Enumeration; import uk.ac.bham.clg.cue.corpus.Cue; import uk.ac.bham.clg.cue.corpus.Item; import uk.ac.bham.clg. |
ac.bham.clg.cue.corpus.Cue; import uk.ac.bham.clg.cue.corpus.Item; import uk.ac.bham.clg.cue.corpus.query.ParseError; public class
|
Concordancer |
{ private Cue data = null; public Concordancer() { data = new Cue(); // select ALL available corpora data.addCorpora(data.getAvailableCorpora()); System.err.println("corpus size overall is "+data. |
import uk.ac.bham.clg.cue.corpus.Item; import uk.ac.bham.clg.cue.corpus.query.ParseError; public class Concordancer { private Cue data = null; public
|
Concordancer( |
) { data = new Cue(); // select ALL available corpora data.addCorpora(data.getAvailableCorpora()); System.err.println("corpus size overall is "+data.getSize()); } public void printKwic(String queryExpr) |
is "+data.getSize()); } public void printKwic(String queryExpr) { try { Enumeration result = data.query(queryExpr); while(result.hasMoreElements()) { Item instance = (Item)result.nextElement(); // print 70 character
|
concordance |
line System.out.println(instance.getKwic(70)); } } catch(ParseError e) { System.err.println("Illegal Query Expression: "+e); } } public static void main(String args[]) { Concordancer conc |
character concordance line System.out.println(instance.getKwic(70)); } } catch(ParseError e) { System.err.println("Illegal Query Expression: "+e); } } public static void main(String args[]) {
|
Concordancer |
conc = new Concordancer(); if(args.length >= 1) conc.printKwic(args[0]); } } This in fact is all you need for a concordancer. You might want to |
System.out.println(instance.getKwic(70)); } } catch(ParseError e) { System.err.println("Illegal Query Expression: "+e); } } public static void main(String args[]) { Concordancer conc = new
|
Concordancer( |
); if(args.length >= 1) conc.printKwic(args[0]); } } This in fact is all you need for a concordancer. You might want to add better error |
void main(String args[]) { Concordancer conc = new Concordancer(); if(args.length >= 1) conc.printKwic(args[0]); } } This in fact is all you need for a
|
concordancer. |
You might want to add better error checking and control of the number of lines printed in order to turn it into a usable program. |
same sentence. Note: in proximity searches a space serves as the AND operator. Select a Results Format: A. (Default) Concordance Report (300 characters plus) B.
|
KWIC |
Report (a single line of text) C. Frequency by Title Please direct comments or queries about this service to ets@lib.uchicago.edu General User |
Default) 4.2 Proximity Searching in the Same Sentence or Paragraph 5. Selecting a Results Format 5.1. Concordance Report (300 characters plus) 5.2.
|
KWIC |
Report (a single line of text) 5.3. Frequency by Title 5.4. Navigating Documents from Word Searches 6. Getting More Help Database-Specific Searching |
words or fewer exactly in the same sentence. Note: in proximity searches a space serves as the AND operator. Select a Results Format: A. (Default)
|
Concordance |
Report (300 characters plus) B. KWIC Report (a single line of text) C. Frequency by Title Please direct comments or queries about this service to |
4.1 Single Term and Phrase Search (Default) 4.2 Proximity Searching in the Same Sentence or Paragraph 5. Selecting a Results Format 5.1.
|
Concordance |
Report (300 characters plus) 5.2. KWIC Report (a single line of text) 5.3. Frequency by Title 5.4. Navigating Documents from Word Searches |
of all occurrences of particular words, and the contexts in which they occur. Such lists are called a concordance, or a 'key word in context' (
|
KWIC) |
list. Here I have taken the transliteration of Geoff's and made such a list, using the concordance program available from the Summer Institute of |
Intro to
|
concordance |
| Home | Concordance: Ai , a , w , bp , fm , n , r , hH , xX , sz , Sqk , gt , TdD | Concordance I n the analysis of texts, it is often |
Intro to concordance | Home |
|
Concordance: |
Ai , a , w , bp , fm , n , r , hH , xX , sz , Sqk , gt , TdD | Concordance I n the analysis of texts, it is often useful to |
Intro to concordance | Home | Concordance: Ai , a , w , bp , fm , n , r , hH , xX , sz , Sqk , gt , TdD |
|
Concordance |
I n the analysis of texts, it is often useful to have a list of all occurrences of particular words, and the contexts in which |
is often useful to have a list of all occurrences of particular words, and the contexts in which they occur. Such lists are called a
|
concordance, |
or a 'key word in context' (KWIC) list. Here I have taken the transliteration of Geoff's and made such a list, using the concordance |
concordance, or a 'key word in context' (KWIC) list. Here I have taken the transliteration of Geoff's and made such a list, using the
|
concordance |
program available from the Summer Institute of Linguistics (see below). The list is rather long, so I have broken it up into sections (see links |
Look it up in the vocabulary (clickable, or general). C omments and criticisms are welcome as I hope to constantly improve this site. Conc . A
|
Concordance |
Generator for the Macintosh. Version 1.80 John Thomson Copyright © 19891996 John Thomsonand the Summer Institute of Linguistics Academic Computing Department (Conc project) 7500 W. |
same sentence. Note: in proximity searches a space serves as the AND operator. Select a Results Format: A. (Default) Concordance Report (300 characters plus) B.
|
KWIC |
Report (a single line of text) C. Frequency by Title For questions or comments concerning the Project please contact: Drew E. VandeCreek, Director, Abraham Lincoln |
the tag END OF REPORT, press your WWW Reload button to retrieve the rest of the results added since you first started viewing results. B.
|
KWIC |
("Quick") Report As in a Concordance Report, a KWIC (Key Word in Context) Report indicates the number of texts searched, the terms searched for in |
button to retrieve the rest of the results added since you first started viewing results. B. KWIC ("Quick") Report As in a Concordance Report, a
|
KWIC |
(Key Word in Context) Report indicates the number of texts searched, the terms searched for in the defined corpus, and the total number of occurrences |
indicates the number of texts searched, the terms searched for in the defined corpus, and the total number of occurrences in the defined corpus. A
|
KWIC |
Report differs from a Concordance Report in that it limits the context displayed to only some ten words of text for each occurrence. As in |
compared to others' works, you could use this function. Any definable corpus or search can be used in generating this report. Note: Unlike Concordance and
|
KWIC |
reports, this report does not display text. Return to top of page. For questions or comments concerning the Project please contact: Drew E. VandeCreek, Director, |
words or fewer exactly in the same sentence. Note: in proximity searches a space serves as the AND operator. Select a Results Format: A. (Default)
|
Concordance |
Report (300 characters plus) B. KWIC Report (a single line of text) C. Frequency by Title For questions or comments concerning the Project please contact: |
g., ï = i) To search regardless of accent use uppercase letters (e.g., to search naïveté regardless of accents type naIvetE ). III. Output Options A.
|
Concordance |
Reports Concordance reporting is the default output option. This report indicates the number of texts searched, the terms searched for in the defined corpus, and |
i) To search regardless of accent use uppercase letters (e.g., to search naïveté regardless of accents type naIvetE ). III. Output Options A. Concordance Reports
|
Concordance |
reporting is the default output option. This report indicates the number of texts searched, the terms searched for in the defined corpus, and the total |
your WWW Reload button to retrieve the rest of the results added since you first started viewing results. B. KWIC ("Quick") Report As in a
|
Concordance |
Report, a KWIC (Key Word in Context) Report indicates the number of texts searched, the terms searched for in the defined corpus, and the total |
searched, the terms searched for in the defined corpus, and the total number of occurrences in the defined corpus. A KWIC Report differs from a
|
Concordance |
Report in that it limits the context displayed to only some ten words of text for each occurrence. As in a Concordance report, clicking on |
differs from a Concordance Report in that it limits the context displayed to only some ten words of text for each occurrence. As in a
|
Concordance |
report, clicking on the short citation reference will retrieve full context with initial key word highlighted. In cases where a search finds more than twenty- |
works as compared to others' works, you could use this function. Any definable corpus or search can be used in generating this report. Note: Unlike
|
Concordance |
and KWIC reports, this report does not display text. Return to top of page. For questions or comments concerning the Project please contact: Drew E. |
integrated standard format. The proposed format encapsulates the Digital Imaging Groups Flashpix?s features of independent-resolution, independent size, metadata, and an unambiguous color model.
|
KWIC |
(KeyWord In Context) is a simple printed index for textual material in which keywords in the text are sorted alphabetically and presented linearly, surrounded by |
link methods), which produce a single layer of clusters, although clusters may overlap (i.e., some items may occur in more than one cluster). (1)
|
Concordance |
, or inverted list, is a data structure for indexing textual data records by the substantive terms or keywords associated with each record. The inverted list |
access to records in the data set. (1) An index is NOT a list of the all the terms in a data set (See also
|
Concordance) |
. Input (imaging) hardware includes the scanner, monitor/display device, computer network or PC, and storage device. Imaging software comprises capture software that works with the |
Old English Part of the Helsinki Corpus SATORU TSUKAMOTO 79 PDF Collocations as a Source of Variation in English SHUNJI YAMAZAKI 93 PDF Courseware Reviews
|
KWIC |
Concordance for Windows Ver. 2.0 SATORU TSUKAMOTO 117 PDF WordBasic for Text Analysis AKIKO INAKI 125 PDF JAPAN ASSOCIATION FOR ENGLISH CORPUS STUDIES |
English Part of the Helsinki Corpus SATORU TSUKAMOTO 79 PDF Collocations as a Source of Variation in English SHUNJI YAMAZAKI 93 PDF Courseware Reviews KWIC
|
Concordance |
for Windows Ver. 2.0 SATORU TSUKAMOTO 117 PDF WordBasic for Text Analysis AKIKO INAKI 125 PDF JAPAN ASSOCIATION FOR ENGLISH CORPUS STUDIES |
to perform a machine-assisted lemmatization. Most of the earliest use of computers in the humanities involved the production of unlemmatized concordances. Early on the
|
KWIC |
concordance format was developed. "KWIC" stands for "Keyword in Context", and an typical excerpt is shown below: sceptic (11) [1,47] abstractions. In vain would |
lemmatization. Most of the earliest use of computers in the humanities involved the production of unlemmatized concordances. Early on the KWIC concordance format was developed. "
|
KWIC" |
stands for "Keyword in Context", and an typical excerpt is shown below: sceptic (11) [1,47] abstractions. In vain would the sceptic make a distinction |
Scottish Philosopher David Hume's Dialogues Concerning Natural Religion ) is listed in alphabetical order. In the excerpt we can see the portion of the entire
|
KWIC |
concordance beginning with the word form "sceptic", and "sceptical". Each word form, called a headword , is followed by its occurrences . Each occurrence, in turn, is |
headword , is followed by its occurrences . Each occurrence, in turn, is given on a separate line consisting, first, of some "reference information" that helps the
|
KWIC |
user locate the occurrence in the full text, and then by a brief excerpt that shows the word in its context - hence the name "Keyword |
occurrence in the full text, and then by a brief excerpt that shows the word in its context - hence the name "Keyword in Context", or
|
KWIC. |
In this example, the reference information is enclosed in square brackets and gives the "part number" that the word occurs in, and a page number |
of dollars. The computer production of a concordance was still a time consuming task. The author recalls assisting one academic who wanted to produce a
|
KWIC |
concordance of the work of a particular Latin author in the late 1970s. The scholar was able to purchase the text, so she didn't |
Nonetheless, in spite of this problem, a number of interesting and useful applications have appeared which one way or another work around this limitation. The
|
Concordance |
The first tool of computer-based analysis was the "Concordance" - a tool that was transformed by the computer, but originated in methods that go back |
and useful applications have appeared which one way or another work around this limitation. The Concordance The first tool of computer-based analysis was the "
|
Concordance" |
- a tool that was transformed by the computer, but originated in methods that go back to the middle ages. The concordance grew out of medieval |
based analysis was the "Concordance" - a tool that was transformed by the computer, but originated in methods that go back to the middle ages. The
|
concordance |
grew out of medieval biblical scholarship that tried to find parallels between the Old and New Testaments by finding places where the words in the |
that pointed to all (or at least many) occurrences of those words in the different books of the Bible. Thus was started the early thematic
|
concordance, |
which named the major people, places, things and ideas that appeared in the Bible. Although the first such Biblical concordances were first created in medieval |
was started the early thematic concordance, which named the major people, places, things and ideas that appeared in the Bible. Although the first such Biblical
|
concordances |
were first created in medieval times, they have never gone out of fashion. As a boy, for example, I was given at Sunday School a |
created in medieval times, they have never gone out of fashion. As a boy, for example, I was given at Sunday School a then popular
|
Concordance |
of the Bible developed by the Rev. W.M. Clow. I don't know when it was created, but from the wording in the introduction |
thee Deut. 31: 6, thy Good, he it is that doth g. Ruth 1: 15, whither thou g., I will go. [...] The editor of this
|
concordance |
didn't attempt to list all occurrences of all the words in the Bible. Function words such as "a" or "for" are not present at |
are listed - only those which were considered significant by the editor. The editor does not tell us about the labour involved in producing such a
|
concordance, |
but it was undoubtedly large, since all occurrences would be recorded and ordered by hand. When done this way concordance production could become the life' |
involved in producing such a concordance, but it was undoubtedly large, since all occurrences would be recorded and ordered by hand. When done this way
|
concordance |
production could become the life's work of a scholar and his team of researchers! With the work of Roberta Busa as early as the |
Roberta Busa as early as the late 1940's, we have the first computer-assisted work in the humanities. Actually, Busa decided to produce a
|
concordance |
by machine of the complete writings of the Medieval scholar Thomas Acquinas for fundamentally scholarly (in this case, philosphical) reasons! His doctoral thesis (defended in |
brings together many different texts and therefore cannot be identified with a unique and coherent communicative event; the citations in a corpus - expandable from the
|
KWIC |
format to include n number of words - remain fragments of text and the significant elements in a corpus are the patterns of repetition and patterns |
horizontally, from left to right, paying attention to the boundaries between larger units such as clauses, sentences and paragraphs. A corpus, examined at first in
|
KWIC |
format with the node word aligned in the centre, will be read vertically, scanning for the repeated patterns present in the co-text of the |
a hypothesis to account for these facts; this in turn will lead to a generalisation based on the evidence of the repeated patterns in the
|
concordance; |
the last step will be the unification of these observations in a theoretical statement. Given that a corpus is a collection of texts, the aim |
evidence, made possible by the new possibility of accessing simultaneously the individual instance, which can be read and expanded on the horizontal axis of the
|
concordance |
[4] , and the social practice retrievable in the repeated patterns of co-selection on the vertical axis of the concordance. Here, frequency of occurrence is |
the horizontal axis of the concordance [4] , and the social practice retrievable in the repeated patterns of co-selection on the vertical axis of the
|
concordance. |
Here, frequency of occurrence is indicative of frequency of use and this gives a good basis to evaluate the profile of a specific word, structure |
to be identified and analysed in order to make statements of meaning. Collocation and colligation are both formal features of a text and the alphabetised
|
concordance |
lends itself remarkably well to the identification of such patterns. The Firthian model, which starts by identifying formal textual features and proceeds to correlate them |
between a conversation and its cultural context. In the specific case of language teaching, the identification and close evaluation of repeated language events in the
|
concordance |
has the purpose of exposing the students to both linguistic and cultural observations. We can conclude by saying that the way a contextual theory of |
terminology, technical glossaries, etc.; statistical data; synonyms, antonyms, hypernyms, pertainyms; phrase lists; etc.. Tools: lexical database management tools; lexical query languages; text analysis tools (concordance,
|
KWIC, |
statistical analysis, collocation analysis, etc.); SGML tools (particularly tuned to dictionary encoding); parsers; morphological analyzers; user interfaces to dictionaries; lexical workbenches; and dictionary definition sense |
specialized terminology, technical glossaries, etc.; statistical data; synonyms, antonyms, hypernyms, pertainyms; phrase lists; etc.. Tools: lexical database management tools; lexical query languages; text analysis tools (
|
concordance, |
KWIC, statistical analysis, collocation analysis, etc.); SGML tools (particularly tuned to dictionary encoding); parsers; morphological analyzers; user interfaces to dictionaries; lexical workbenches; and dictionary definition |
highly referential world of newspapers, magazines and books. The concordancer in its more linguistic uses was not widely understood: for instance, the possibility of extending
|
kwic |
searches to look at morphology . Only one student wondered whether it might be useful to use a concordancer to look for inflexions, and for infinitive |
web site. (http://www-iet.open.ac.uk/courses/lexica/lexica.html) c) Advice about the aims of the Project, the use of dictionary and
|
concordancer |
and the role of the tutors was provided on the Project web site. (http://www-iet.open.ac.uk/courses/lexica/participants.html) d) Tutorial |
method of learning - I still remember my words after selection and use... ..opportunity for infinite repetition... Negative views tend to concentrate around the texts, the
|
concordancer, |
the Forum and the design of Lexica: Negatives ...texts too easy... ...limitations of texts chosen... ...greater number of texts perhaps including some not directly related |
of texts chosen... ...greater number of texts perhaps including some not directly related to the course... ...I knew most of the words in the texts... ..
|
concordancer |
is a tool for advanced linguists ..structure of forum difficult to pick up...needs more main conferences or threads... ...web site difficult and slow to |
its relevance. Some students, while reporting difficulties with the task, found a practical way forward, and came close to being able to talk about polysemy:
|
Concordancer |
This was a totally unfamiliar tool, but one which captivated students at first. Queries were not about how to use it, or why, but about |
the corpus was not big enough to provide alternative examples of more unusual words and expressions). The most successful tools were the dictionary and the
|
concordancer |
(when used as a dictionary) which deal with meaning and 'real' referents. The Web was also appreciated as a vehicle for pursuing the student's |
Web was also appreciated as a vehicle for pursuing the student's own learning via the highly referential world of newspapers, magazines and books. The
|
concordancer |
in its more linguistic uses was not widely understood: for instance, the possibility of extending kwic searches to look at morphology . Only one student wondered |
understood: for instance, the possibility of extending kwic searches to look at morphology . Only one student wondered whether it might be useful to use a
|
concordancer |
to look for inflexions, and for infinitive forms of verbs. Form-focused work did not generally appeal, however. The least successful tool, the grouping module, |
whole understood . Its relevance was queried several times. Familiar tools and resources (dictionary, library, bookshop or newstands) are reassuring, whereas those demanding more abstract thought (
|
concordancer, |
grouping tool) are intimidating. Having to acquire Web skills, and to combine them with Lexica procedures, puts a learning burden on students, but this is |
to the way you approach vocabulary learning: SELECTING vocabulary yourself, from the texts Making NOTES on selected items Putting the items into GROUPS Using the
|
CONCORDANCER |
Testing with the CONTEXT clue Testing with the NOTES clue Testing with the GROUPS clue 6. Please tick any of the areas in which you |
other than Shakespeare); it will let you search for the collocates of words you think important, and will display these in what is called a
|
KWIC |
format (key word in context). TACT, which has more features (and more subprograms) will let you search for groups of words, for parts of words, |
ones I've found so far are the Oxford Text Archive, the University of Virginia Electronic Text Center, and the Gutenberg Project. The most promising
|
concordance |
software packages that I've so far discovered are Michael Barlow's Monoconc and the University of Toronto's "TACT" ("Text-Analysis Computing Tools"). The |
The simplicity of my tag-counter program is in contrast to another SPITBOL program I call CONCORD; it generates a complete key-word-in-context (
|
KWIC) |
concordance for a text. Click here to read note 1. Figure 2 shows an extremely small part of CONCORD's output for Herman Melville's |
read note 1. Figure 2 shows an extremely small part of CONCORD's output for Herman Melville's Moby-Dick. In order to produce a
|
KWIC |
concordance for that novel, CONCORD identified each of the 210,349 words of running text, and it stored the words in a table along with |
with the location of each word; it sorted them in alphabetical order, and it created an output file. CONCORD's output file containing a full
|
KWIC |
concordance of Moby-Dick is over eighteen megabytes. As can be seen in Figure 2, CONCORD's output has each word centered in its context |
numeric computing available for a microcomputer. Only about five minutes is needed for CONCORD to produce an 11. Click here to read note 2. megabyte
|
KWIC |
concordance for Lord Jim when it is run on a (now, rather modest) microcomputer containing an 80486-25 MHZ processor. If it were printed, the |
Whale made a sudden rush among 16429.6 rpendicularly from the sea, the WHITE Whale dashed his broad forehead Figure 2. Output from CONCORD: a
|
KWIC |
concordance program written in SPITBOL. |
simplicity of my tag-counter program is in contrast to another SPITBOL program I call CONCORD; it generates a complete key-word-in-context (KWIC)
|
concordance |
for a text. Click here to read note 1. Figure 2 shows an extremely small part of CONCORD's output for Herman Melville's Moby- |
note 1. Figure 2 shows an extremely small part of CONCORD's output for Herman Melville's Moby-Dick. In order to produce a KWIC
|
concordance |
for that novel, CONCORD identified each of the 210,349 words of running text, and it stored the words in a table along with the |
the location of each word; it sorted them in alphabetical order, and it created an output file. CONCORD's output file containing a full KWIC
|
concordance |
of Moby-Dick is over eighteen megabytes. As can be seen in Figure 2, CONCORD's output has each word centered in its context (of |
computing available for a microcomputer. Only about five minutes is needed for CONCORD to produce an 11. Click here to read note 2. megabyte KWIC
|
concordance |
for Lord Jim when it is run on a (now, rather modest) microcomputer containing an 80486-25 MHZ processor. If it were printed, the 11. |
Jim when it is run on a (now, rather modest) microcomputer containing an 80486-25 MHZ processor. If it were printed, the 11.2 megabyte
|
concordance |
would require about 2,500 sheets of paper: five reams. Thus, this SPITBOL-386 program can produce about five hundred pages of output per minute |
made a sudden rush among 16429.6 rpendicularly from the sea, the WHITE Whale dashed his broad forehead Figure 2. Output from CONCORD: a KWIC
|
concordance |
program written in SPITBOL. |
as > grep or Norton's TS which can search through multiple files and > multiple directories to locate a text. Nor can they be processed by >
|
KWIC |
concordance software. True. But if these observations are relevant or not depends on what the goals are. If the goal is preservation, existing tools may |
grep or Norton's TS which can search through multiple files and > multiple directories to locate a text. Nor can they be processed by > KWIC
|
concordance |
software. True. But if these observations are relevant or not depends on what the goals are. If the goal is preservation, existing tools may be |
field relatively frequently. The concordancer searches for all instances in the text of a search word. The user can specify the output to be a
|
KWIC |
concordance (key word in context) or a full sentence concordance. The collocation operation looks for other words in the vicinity of a search word, within |
the present study. The main operations are the following: Preprocessing sentence delimiting part of speech tagging finding and grouping compound nouns Main Processing frequency operations
|
concordance |
collocations conceptual operations Sentence delimiting is a preprocessing operation that must be performed on a text before it can be used in the TA. This |
for determining potential terms, the assumption being that a text treating a given subject field will use the terms from that field relatively frequently. The
|
concordancer |
searches for all instances in the text of a search word. The user can specify the output to be a KWIC concordance (key word in |
relatively frequently. The concordancer searches for all instances in the text of a search word. The user can specify the output to be a KWIC
|
concordance |
(key word in context) or a full sentence concordance. The collocation operation looks for other words in the vicinity of a search word, within a |
the text of a search word. The user can specify the output to be a KWIC concordance (key word in context) or a full sentence
|
concordance. |
The collocation operation looks for other words in the vicinity of a search word, within a range of five words on either side. The output |
and Thomas Paine. Complete works of Robert G. Ingersoll. True Seeker - will allow you to search the Bahá'í writings using a KeyWord In Context (
|
KWIC) |
search. World Scripture - comparative anthology of themes in sacred texts by Dr. Andrew Wilson. Copyright © 2001 Yahoo! Inc. - Company Information - Suggest a Site - FAQ |
religion. Bahá'í Academics Resource Library - extensive collection of Bahá'í texts. Bahá'í Writings - works of The Báb, Bahá'u'lláh, and other authors.
|
Concordances |
of Scriptures - full text and word search for the Bible, Apocrypha, Koran, Bhagavad-Gita, Tao Te Chung, and others. Internet Sacred Text Archive - archive of |
term) from language A, and the program then finds and displays all the instances of the search term. The concordance results are typically displayed in
|
KWIC |
format, i.e., with the search word in the centre of the window, along with a context of preceding and following words. In addition, the |
in terms of a schema-based approach to grammatical knowledge described in Barlow and Kemmer (1994) and Barlow (1996). A brief description of a parallel
|
concordance |
program is also included. Keywords: translation schema concordance bilingual text 1. Introduction The relation of form and meaning is at the core of language study, |
grammatical knowledge described in Barlow and Kemmer (1994) and Barlow (1996). A brief description of a parallel concordance program is also included. Keywords: translation schema
|
concordance |
bilingual text 1. Introduction The relation of form and meaning is at the core of language study, whether for the lexicographer grappling with homonymy and |
approaches issues in translation via a modest exploration of the nature of form-meaning links from a linguistic viewpoint and a brief description of a
|
concordance |
program that can be used to extract useful information about the process of translation. The term translation equivalence has an uneasy feel about it, based |
and discuss the information to be derived from bilingual corpora. One way to extract the information inherent in such corpora is by using a parallel
|
concordance |
program such as ParaConc for Windows . This software can be used to investigate various aspects of translation, including translation equivalence, as described in the following |
This software can be used to investigate various aspects of translation, including translation equivalence, as described in the following section. 2. Bilingual Concordancing Like other
|
concordance |
programs, ParaConc for Windows facilitates research into the lexical, syntactic, and semantic patterns of a language. It differs from other concordancers in that it is |
Bilingual Concordancing Like other concordance programs, ParaConc for Windows facilitates research into the lexical, syntactic, and semantic patterns of a language. It differs from other
|
concordancers |
in that it is designed to work with parallel texts, i.e., texts in two languages that are translations and are aligned, typically sentence by |
or phrase (i.e., a search term) from language A, and the program then finds and displays all the instances of the search term. The
|
concordance |
results are typically displayed in KWIC format, i.e., with the search word in the centre of the window, along with a context of preceding |
at least not in the sentence that is displayed. Let us briefly look at some data to illustrate the information made available by a parallel
|
concordancer. |
If the English section of an English-French parallel corpus is searched for the word head , then the software will find and display the first |
wasn't someone you could tackle head on. I just said to him in a faint voi... The search term is centred and consequently, the
|
concordance |
line may be cut off in mid-word. Since we expect texts to consist of complete sentences or at least complete words, this format can |
interpret these results it is important to remember that the French sentence matches the English sentence containing the search term head , and not the complete
|
concordance |
line. The results obtained from this search can be examined to see the relationship between the English search term along with its context and the |
