-
Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004)
0.41
0.4050102 = product of:
0.5670143 = sum of:
0.034518216 = product of:
0.17259108 = sum of:
0.17259108 = weight(_text_:3a in 562) [ClassicSimilarity], result of:
0.17259108 = score(doc=562,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.2 = coord(1/5)
0.17259108 = weight(_text_:2f in 562) [ClassicSimilarity], result of:
0.17259108 = score(doc=562,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.17259108 = weight(_text_:2f in 562) [ClassicSimilarity], result of:
0.17259108 = score(doc=562,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.17259108 = weight(_text_:2f in 562) [ClassicSimilarity], result of:
0.17259108 = score(doc=562,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.0147228 = product of:
0.0294456 = sum of:
0.0294456 = weight(_text_:22 in 562) [ClassicSimilarity], result of:
0.0294456 = score(doc=562,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.23214069 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.5 = coord(1/2)
0.71428573 = coord(5/7)
- Content
- Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
- Date
- 8. 1.2013 10:22:32
-
Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012)
0.39
0.39343736 = product of:
0.5508123 = sum of:
0.018316243 = product of:
0.045790605 = sum of:
0.02197135 = weight(_text_:retrieval in 563) [ClassicSimilarity], result of:
0.02197135 = score(doc=563,freq=2.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.20052543 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.023819257 = weight(_text_:system in 563) [ClassicSimilarity], result of:
0.023819257 = score(doc=563,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.20878783 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.4 = coord(2/5)
0.17259108 = weight(_text_:2f in 563) [ClassicSimilarity], result of:
0.17259108 = score(doc=563,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.17259108 = weight(_text_:2f in 563) [ClassicSimilarity], result of:
0.17259108 = score(doc=563,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.17259108 = weight(_text_:2f in 563) [ClassicSimilarity], result of:
0.17259108 = score(doc=563,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.0147228 = product of:
0.0294456 = sum of:
0.0294456 = weight(_text_:22 in 563) [ClassicSimilarity], result of:
0.0294456 = score(doc=563,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.23214069 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.5 = coord(1/2)
0.71428573 = coord(5/7)
- Abstract
- In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.
- Content
- A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
- Date
- 10. 1.2013 19:22:47
-
Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
0.32
0.31559512 = product of:
0.55229145 = sum of:
0.034518216 = product of:
0.17259108 = sum of:
0.17259108 = weight(_text_:3a in 862) [ClassicSimilarity], result of:
0.17259108 = score(doc=862,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 862, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.2 = coord(1/5)
0.17259108 = weight(_text_:2f in 862) [ClassicSimilarity], result of:
0.17259108 = score(doc=862,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 862, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.17259108 = weight(_text_:2f in 862) [ClassicSimilarity], result of:
0.17259108 = score(doc=862,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 862, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.17259108 = weight(_text_:2f in 862) [ClassicSimilarity], result of:
0.17259108 = score(doc=862,freq=2.0), product of:
0.3070917 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03622214 = queryNorm
0.56201804 = fieldWeight in 862, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.5714286 = coord(4/7)
- Source
- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
-
Schwarz, C.: THESYS: Thesaurus Syntax System : a fully automatic thesaurus building aid (1988)
0.01
0.011013014 = product of:
0.03854555 = sum of:
0.02136895 = product of:
0.053422377 = sum of:
0.025633242 = weight(_text_:retrieval in 1361) [ClassicSimilarity], result of:
0.025633242 = score(doc=1361,freq=2.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.23394634 = fieldWeight in 1361, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=1361)
0.027789133 = weight(_text_:system in 1361) [ClassicSimilarity], result of:
0.027789133 = score(doc=1361,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.2435858 = fieldWeight in 1361, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0546875 = fieldNorm(doc=1361)
0.4 = coord(2/5)
0.0171766 = product of:
0.0343532 = sum of:
0.0343532 = weight(_text_:22 in 1361) [ClassicSimilarity], result of:
0.0343532 = score(doc=1361,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.2708308 = fieldWeight in 1361, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=1361)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- THESYS is based on the natural language processing of free-text databases. It yields statistically evaluated correlations between words of the database. These correlations correspond to traditional thesaurus relations. The person who has to build a thesaurus is thus assisted by the proposals made by THESYS. THESYS is being tested on commercial databases under real world conditions. It is part of a text processing project at Siemens, called TINA (Text-Inhalts-Analyse). Software from TINA is actually being applied and evaluated by the US Department of Commerce for patent search and indexing (REALIST: REtrieval Aids by Linguistics and STatistics)
- Date
- 6. 1.1999 10:22:07
-
Byrne, C.C.; McCracken, S.A.: ¬An adaptive thesaurus employing semantic distance, relational inheritance and nominal compound interpretation for linguistic support of information retrieval (1999)
0.01
0.01092404 = product of:
0.03823414 = sum of:
0.00878854 = product of:
0.0439427 = sum of:
0.0439427 = weight(_text_:retrieval in 4483) [ClassicSimilarity], result of:
0.0439427 = score(doc=4483,freq=2.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.40105087 = fieldWeight in 4483, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.09375 = fieldNorm(doc=4483)
0.2 = coord(1/5)
0.0294456 = product of:
0.0588912 = sum of:
0.0588912 = weight(_text_:22 in 4483) [ClassicSimilarity], result of:
0.0588912 = score(doc=4483,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.46428138 = fieldWeight in 4483, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.09375 = fieldNorm(doc=4483)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Date
- 15. 3.2000 10:22:37
-
Doszkocs, T.E.; Zamora, A.: Dictionary services and spelling aids for Web searching (2004)
0.01
0.01018518 = product of:
0.03564813 = sum of:
0.018297145 = product of:
0.045742862 = sum of:
0.025893483 = weight(_text_:retrieval in 2541) [ClassicSimilarity], result of:
0.025893483 = score(doc=2541,freq=4.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.23632148 = fieldWeight in 2541, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=2541)
0.01984938 = weight(_text_:system in 2541) [ClassicSimilarity], result of:
0.01984938 = score(doc=2541,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.17398985 = fieldWeight in 2541, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0390625 = fieldNorm(doc=2541)
0.4 = coord(2/5)
0.017350987 = product of:
0.034701973 = sum of:
0.034701973 = weight(_text_:22 in 2541) [ClassicSimilarity], result of:
0.034701973 = score(doc=2541,freq=4.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.27358043 = fieldWeight in 2541, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=2541)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- The Specialized Information Services Division (SIS) of the National Library of Medicine (NLM) provides Web access to more than a dozen scientific databases on toxicology and the environment on TOXNET . Search queries on TOXNET often include misspelled or variant English words, medical and scientific jargon and chemical names. Following the example of search engines like Google and ClinicalTrials.gov, we set out to develop a spelling "suggestion" system for increased recall and precision in TOXNET searching. This paper describes development of dictionary technology that can be used in a variety of applications such as orthographic verification, writing aid, natural language processing, and information storage and retrieval. The design of the technology allows building complex applications using the components developed in the earlier phases of the work in a modular fashion without extensive rewriting of computer code. Since many of the potential applications envisioned for this work have on-line or web-based interfaces, the dictionaries and other computer components must have fast response, and must be adaptable to open-ended database vocabularies, including chemical nomenclature. The dictionary vocabulary for this work was derived from SIS and other databases and specialized resources, such as NLM's Unified Medical Language Systems (UMLS) . The resulting technology, A-Z Dictionary (AZdict), has three major constituents: 1) the vocabulary list, 2) the word attributes that define part of speech and morphological relationships between words in the list, and 3) a set of programs that implements the retrieval of words and their attributes, and determines similarity between words (ChemSpell). These three components can be used in various applications such as spelling verification, spelling aid, part-of-speech tagging, paraphrasing, and many other natural language processing functions.
- Date
- 14. 8.2004 17:22:56
- Source
- Online. 28(2004) no.3, S.22-29
-
Bian, G.-W.; Chen, H.-H.: Cross-language information access to multilingual collections on the Internet (2000)
0.01
0.009439726 = product of:
0.03303904 = sum of:
0.018316243 = product of:
0.045790605 = sum of:
0.02197135 = weight(_text_:retrieval in 4436) [ClassicSimilarity], result of:
0.02197135 = score(doc=4436,freq=2.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.20052543 = fieldWeight in 4436, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=4436)
0.023819257 = weight(_text_:system in 4436) [ClassicSimilarity], result of:
0.023819257 = score(doc=4436,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.20878783 = fieldWeight in 4436, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.046875 = fieldNorm(doc=4436)
0.4 = coord(2/5)
0.0147228 = product of:
0.0294456 = sum of:
0.0294456 = weight(_text_:22 in 4436) [ClassicSimilarity], result of:
0.0294456 = score(doc=4436,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.23214069 = fieldWeight in 4436, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=4436)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- Language barrier is the major problem that people face in searching for, retrieving, and understanding multilingual collections on the Internet. This paper deals with query translation and document translation in a Chinese-English information retrieval system called MTIR. Bilingual dictionary and monolingual corpus-based approaches are adopted to select suitable tranlated query terms. A machine transliteration algorithm is introduced to resolve proper name searching. We consider several design issues for document translation, including which material is translated, what roles the HTML tags play in translation, what the tradeoff is between the speed performance and the translation performance, and what from the translated result is presented in. About 100.000 Web pages translated in the last 4 months of 1997 are used for quantitative study of online and real-time Web page translation
- Date
- 16. 2.2000 14:22:39
-
Mauldin, M.L.: Conceptual information retrieval : a case study in adaptive partial parsing (1991)
0.01
0.008118572 = product of:
0.056829996 = sum of:
0.056829996 = product of:
0.14207499 = sum of:
0.097160965 = weight(_text_:retrieval in 121) [ClassicSimilarity], result of:
0.097160965 = score(doc=121,freq=22.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.88675684 = fieldWeight in 121, product of:
4.690416 = tf(freq=22.0), with freq of:
22.0 = termFreq=22.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=121)
0.044914022 = weight(_text_:system in 121) [ClassicSimilarity], result of:
0.044914022 = score(doc=121,freq=4.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.3936941 = fieldWeight in 121, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0625 = fieldNorm(doc=121)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- LCSH
- FERRET (Information retrieval system)
Information storage and retrieval
- RSWK
- Freitextsuche / Information Retrieval
Information Retrieval / Expertensystem
Syntaktische Analyse Information Retrieval
- Subject
- Freitextsuche / Information Retrieval
Information Retrieval / Expertensystem
Syntaktische Analyse Information Retrieval
FERRET (Information retrieval system)
Information storage and retrieval
-
Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996)
0.01
0.007423487 = product of:
0.025982203 = sum of:
0.006351802 = product of:
0.03175901 = sum of:
0.03175901 = weight(_text_:system in 6752) [ClassicSimilarity], result of:
0.03175901 = score(doc=6752,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.27838376 = fieldWeight in 6752, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0625 = fieldNorm(doc=6752)
0.2 = coord(1/5)
0.0196304 = product of:
0.0392608 = sum of:
0.0392608 = weight(_text_:22 in 6752) [ClassicSimilarity], result of:
0.0392608 = score(doc=6752,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.30952093 = fieldWeight in 6752, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=6752)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- AutoSlog is a system that addresses the knowledge engineering bottleneck for information extraction. AutoSlog automatically creates domain specific dictionaries for information extraction, given an appropriate training corpus. Describes experiments with AutoSlog in terrorism, joint ventures and microelectronics domains. Compares the performance of AutoSlog across the 3 domains, discusses the lessons learned and presents results from 2 experiments which demonstrate that novice users can generate effective dictionaries using AutoSlog
- Date
- 6. 3.1997 16:22:15
-
Basili, R.; Pazienza, M.T.; Velardi, P.: ¬An empirical symbolic approach to natural language processing (1996)
0.01
0.007423487 = product of:
0.025982203 = sum of:
0.006351802 = product of:
0.03175901 = sum of:
0.03175901 = weight(_text_:system in 6753) [ClassicSimilarity], result of:
0.03175901 = score(doc=6753,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.27838376 = fieldWeight in 6753, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0625 = fieldNorm(doc=6753)
0.2 = coord(1/5)
0.0196304 = product of:
0.0392608 = sum of:
0.0392608 = weight(_text_:22 in 6753) [ClassicSimilarity], result of:
0.0392608 = score(doc=6753,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.30952093 = fieldWeight in 6753, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=6753)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- Describes and evaluates the results of a large scale lexical learning system, ARISTO-LEX, that uses a combination of probabilisitc and knowledge based methods for the acquisition of selectional restrictions of words in sublanguages. Presents experimental data obtained from different corpora in different doamins and languages, and shows that the acquired lexical data not only have practical applications in natural language processing, but they are useful for a comparative analysis of sublanguages
- Date
- 6. 3.1997 16:22:15
-
Haas, S.W.: Natural language processing : toward large-scale, robust systems (1996)
0.01
0.007282694 = product of:
0.025489427 = sum of:
0.0058590267 = product of:
0.029295133 = sum of:
0.029295133 = weight(_text_:retrieval in 7415) [ClassicSimilarity], result of:
0.029295133 = score(doc=7415,freq=2.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.26736724 = fieldWeight in 7415, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=7415)
0.2 = coord(1/5)
0.0196304 = product of:
0.0392608 = sum of:
0.0392608 = weight(_text_:22 in 7415) [ClassicSimilarity], result of:
0.0392608 = score(doc=7415,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.30952093 = fieldWeight in 7415, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=7415)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- State of the art review of natural language processing updating an earlier review published in ARIST 22(1987). Discusses important developments that have allowed for significant advances in the field of natural language processing: materials and resources; knowledge based systems and statistical approaches; and a strong emphasis on evaluation. Reviews some natural language processing applications and common problems still awaiting solution. Considers closely related applications such as language generation and th egeneration phase of machine translation which face the same problems as natural language processing. Covers natural language methodologies for information retrieval only briefly
-
Sembok, T.M.T.; Rijsbergen, C.J. van: SILOL: a simple logical-linguistic document retrieval system (1990)
0.01
0.007243792 = product of:
0.050706543 = sum of:
0.050706543 = product of:
0.12676635 = sum of:
0.07175813 = weight(_text_:retrieval in 6684) [ClassicSimilarity], result of:
0.07175813 = score(doc=6684,freq=12.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.6549133 = fieldWeight in 6684, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0625 = fieldNorm(doc=6684)
0.055008218 = weight(_text_:system in 6684) [ClassicSimilarity], result of:
0.055008218 = score(doc=6684,freq=6.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.48217484 = fieldWeight in 6684, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0625 = fieldNorm(doc=6684)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- Abstract
- Describes a system called SILOL which is based on a logical-linguistic model of document retrieval systems. SILOL uses a shallow semantic translation of natural language texts into a first order predicate representation in performing a document indexing and retrieval process. Some preliminary experiments have been carried out to test the retrieval effectiveness of this system. The results obtained show improvements in the level of retrieval effectiveness, which demonstrate that the approach of using a semantic theory of natural language and logic in document retrieval systems is a valid one
-
Hammwöhner, R.: TransRouter revisited : Decision support in the routing of translation projects (2000)
0.01
0.0071533015 = product of:
0.025036555 = sum of:
0.007859954 = product of:
0.039299767 = sum of:
0.039299767 = weight(_text_:system in 5483) [ClassicSimilarity], result of:
0.039299767 = score(doc=5483,freq=4.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.34448233 = fieldWeight in 5483, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0546875 = fieldNorm(doc=5483)
0.2 = coord(1/5)
0.0171766 = product of:
0.0343532 = sum of:
0.0343532 = weight(_text_:22 in 5483) [ClassicSimilarity], result of:
0.0343532 = score(doc=5483,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.2708308 = fieldWeight in 5483, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=5483)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- This paper gives an outline of the final results of the TransRouter project. In the scope of this project a decision support system for translation managers has been developed, which will support the selection of appropriate routes for translation projects. In this paper emphasis is put on the decision model, which is based on a stepwise refined assessment of translation routes. The workflow of using this system is considered as well
- Date
- 10.12.2000 18:22:35
-
Liddy, E.D.: Natural language processing for information retrieval and knowledge discovery (1998)
0.01
0.006979079 = product of:
0.024426775 = sum of:
0.007250175 = product of:
0.036250874 = sum of:
0.036250874 = weight(_text_:retrieval in 2345) [ClassicSimilarity], result of:
0.036250874 = score(doc=2345,freq=4.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.33085006 = fieldWeight in 2345, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=2345)
0.2 = coord(1/5)
0.0171766 = product of:
0.0343532 = sum of:
0.0343532 = weight(_text_:22 in 2345) [ClassicSimilarity], result of:
0.0343532 = score(doc=2345,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.2708308 = fieldWeight in 2345, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=2345)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- Natural language processing (NLP) is a powerful technology for the vital tasks of information retrieval (IR) and knowledge discovery (KD) which, in turn, feed the visualization systems of the present and future and enable knowledge workers to focus more of their time on the vital tasks of analysis and prediction
- Date
- 22. 9.1997 19:16:05
-
Kay, M.: ¬The proper place of men and machines in language translation (1997)
0.01
0.0064955507 = product of:
0.022734426 = sum of:
0.0055578267 = product of:
0.027789133 = sum of:
0.027789133 = weight(_text_:system in 1178) [ClassicSimilarity], result of:
0.027789133 = score(doc=1178,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.2435858 = fieldWeight in 1178, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0546875 = fieldNorm(doc=1178)
0.2 = coord(1/5)
0.0171766 = product of:
0.0343532 = sum of:
0.0343532 = weight(_text_:22 in 1178) [ClassicSimilarity], result of:
0.0343532 = score(doc=1178,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.2708308 = fieldWeight in 1178, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=1178)
0.5 = coord(1/2)
0.2857143 = coord(2/7)
- Abstract
- Machine translation stands no chance of filling actual needs for translation because, although there has been progress in relevant areas of computer science, advance in linguistics have not touched the core problems. Cooperative man-machine systems need to be developed, Proposes a translator's amanuensis, incorporating into a word processor some simple facilities peculiar to translation. Gradual enhancements of such a system could lead to the original goal of machine translation
- Date
- 31. 7.1996 9:22:19
-
Yannakoudakis, E.J.; Daraki, J.J.: Lexical clustering and retrieval of bibliographic records (1994)
0.01
0.0063383174 = product of:
0.04436822 = sum of:
0.04436822 = product of:
0.11092055 = sum of:
0.06278836 = weight(_text_:retrieval in 1045) [ClassicSimilarity], result of:
0.06278836 = score(doc=1045,freq=12.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.5730491 = fieldWeight in 1045, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=1045)
0.048132192 = weight(_text_:system in 1045) [ClassicSimilarity], result of:
0.048132192 = score(doc=1045,freq=6.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.42190298 = fieldWeight in 1045, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0546875 = fieldNorm(doc=1045)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- Abstract
- Presents a new system that enables users to retrieve catalogue entries on the basis of theri lexical similarities and to cluster records in a dynamic fashion. Describes the information retrieval system developed by the Department of Informatics, Athens University of Economics and Business, Greece. The system also offers the means for cyclic retrieval of records from each cluster while allowing the user to define the field to be used in each case. The approach is based on logical keys which are derived from pertinent bibliographic fields and are used for all clustering and information retrieval functions
- Source
- Information retrieval: new systems and current research. Proceedings of the 15th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Glasgow 1993. Ed.: Ruben Leon
-
Beitzel, S.M.; Jensen, E.C.; Chowdhury, A.; Grossman, D.; Frieder, O; Goharian, N.: Fusion of effective retrieval strategies in the same information retrieval system (2004)
0.01
0.006327753 = product of:
0.044294268 = sum of:
0.044294268 = product of:
0.11073567 = sum of:
0.0694795 = weight(_text_:retrieval in 2502) [ClassicSimilarity], result of:
0.0694795 = score(doc=2502,freq=20.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.63411707 = fieldWeight in 2502, product of:
4.472136 = tf(freq=20.0), with freq of:
20.0 = termFreq=20.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=2502)
0.041256163 = weight(_text_:system in 2502) [ClassicSimilarity], result of:
0.041256163 = score(doc=2502,freq=6.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.36163113 = fieldWeight in 2502, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.046875 = fieldNorm(doc=2502)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- Abstract
- Prior efforts have shown that under certain situations retrieval effectiveness may be improved via the use of data fusion techniques. Although these improvements have been observed from the fusion of result sets from several distinct information retrieval systems, it has often been thought that fusing different document retrieval strategies in a single information retrieval system will lead to similar improvements. In this study, we show that this is not the case. We hold constant systemic differences such as parsing, stemming, phrase processing, and relevance feedback, and fuse result sets generated from highly effective retrieval strategies in the same information retrieval system. From this, we show that data fusion of highly effective retrieval strategies alone shows little or no improvement in retrieval effectiveness. Furthermore, we present a detailed analysis of the performance of modern data fusion approaches, and demonstrate the reasons why they do not perform weIl when applied to this problem. Detailed results and analyses are included to support our conclusions.
-
McCune, B.P.; Tong, R.M.; Dean, J.S.: Rubric: a system for rule-based information retrieval (1985)
0.01
0.006273308 = product of:
0.043913152 = sum of:
0.043913152 = product of:
0.109782875 = sum of:
0.06214436 = weight(_text_:retrieval in 1945) [ClassicSimilarity], result of:
0.06214436 = score(doc=1945,freq=4.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.5671716 = fieldWeight in 1945, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.09375 = fieldNorm(doc=1945)
0.047638513 = weight(_text_:system in 1945) [ClassicSimilarity], result of:
0.047638513 = score(doc=1945,freq=2.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.41757566 = fieldWeight in 1945, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.09375 = fieldNorm(doc=1945)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- Footnote
- Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.440-445.
-
Magennis, M.: Expert rule-based query expansion (1995)
0.01
0.0056799245 = product of:
0.03975947 = sum of:
0.03975947 = product of:
0.09939867 = sum of:
0.051266484 = weight(_text_:retrieval in 5181) [ClassicSimilarity], result of:
0.051266484 = score(doc=5181,freq=8.0), product of:
0.109568894 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03622214 = queryNorm
0.46789268 = fieldWeight in 5181, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0546875 = fieldNorm(doc=5181)
0.048132192 = weight(_text_:system in 5181) [ClassicSimilarity], result of:
0.048132192 = score(doc=5181,freq=6.0), product of:
0.11408355 = queryWeight, product of:
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.03622214 = queryNorm
0.42190298 = fieldWeight in 5181, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.1495528 = idf(docFreq=5152, maxDocs=44218)
0.0546875 = fieldNorm(doc=5181)
0.4 = coord(2/5)
0.14285715 = coord(1/7)
- Abstract
- Examines how, for term based free text retrieval, Interactive Query Expansion (IQE) provides better retrieval performance tahn Automatic Query Expansion (AQE) but the performance of IQE depends on the strategy employed by the user to select expansion terms. The aim is to build an expert query expansion system using term selection rules based on expert users' strategies. It is expected that such a system will achieve better performance for novice or inexperienced users that either AQE or IQE. The procedure is to discover expert IQE users' term selection strategies through observation and interrogation, to construct a rule based query expansion (RQE) system based on these and to compare the resulting retrieval performance with that of comparable AQE and IQE systems
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Warner, A.J.: Natural language processing (1987)
0.01
0.0056086862 = product of:
0.0392608 = sum of:
0.0392608 = product of:
0.0785216 = sum of:
0.0785216 = weight(_text_:22 in 337) [ClassicSimilarity], result of:
0.0785216 = score(doc=337,freq=2.0), product of:
0.12684377 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03622214 = queryNorm
0.61904186 = fieldWeight in 337, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.125 = fieldNorm(doc=337)
0.5 = coord(1/2)
0.14285715 = coord(1/7)
- Source
- Annual review of information science and technology. 22(1987), S.79-108
