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Stede, M.: Lexicalization in natural language generation : a survey (1994/95)
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- Abstract
- In natural language generation, a meaning representation of some kind is successively transformed into a sentence or a text. Naturally, a central subtask of this problem is the choice of words, or lexicalization. Proposes 4 major issues that determine how a generator tackles lexicalization, and surveys the contributions that research have made to them. Identifies open problems, and sketches a possible direction for research
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- a
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Barriere, C.: Building a concept hierarchy from corpus analysis (2004)
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Chung, T.M.: ¬A corpus comparison approach for terminology extraction (2003)
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Bernth, A.; McCord, M.; Warburton, K.: Terminology extraction for global content management (2003)
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Czejdo. B.D.; Tucci, R.P.: ¬A dataflow graphical language for database applications (1994)
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- Abstract
- Discusses a graphical language for information retrieval and processing. A lot of recent activity has occured in the area of improving access to database systems. However, current results are restricted to simple interfacing of database systems. Proposes a graphical language for specifying complex applications
- Type
- a
-
Koppel, M.; Akiva, N.; Dagan, I.: Feature instability as a criterion for selecting potential style markers (2006)
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- Abstract
- We introduce a new measure on linguistic features, called stability, which captures the extent to which a language element such as a word or a syntactic construct is replaceable by semantically equivalent elements. This measure may be perceived as quantifying the degree of available "synonymy" for a language item. We show that frequent, but unstable, features are especially useful as discriminators of an author's writing style.
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- a
-
Lawson, V.; Vasconcellos, M.: Forty ways to skin a cat : users report on machine translation (1994)
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- Abstract
- In the most extensive survey of machine translation (MT) use ever performed, explores the responeses to a questionnaire survey of 40 MT users concerning their experiences
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- a
-
McKelvie, D.; Brew, C.; Thompson, H.S.: Uisng SGML as a basis for data-intensive natural language processing (1998)
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- Abstract
- Addresses advantages and disadvantages of SGML-approach compared with a non-SGML database aproach
- Type
- a
-
Rodriguez, H.; Climent, S.; Vossen, P.; Bloksma, L.; Peters, W.; Alonge, A.; Bertagna, F.; Roventini, A.: ¬The top-down strategy for building EuroWordNet : vocabulary coverage, base concept and top ontology (1998)
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Vechtomova, O.: ¬A method for automatic extraction of multiword units representing business aspects from user reviews (2014)
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- Abstract
- The article describes a semi-supervised approach to extracting multiword aspects of user-written reviews that belong to a given category. The method starts with a small set of seed words, representing the target category, and calculates distributional similarity between the candidate and seed words. We compare 3 distributional similarity measures (Lin's, Weeds's, and balAPinc), and a document retrieval function, BM25, adapted as a word similarity measure. We then introduce a method for identifying multiword aspects by using a combination of syntactic rules and a co-occurrence association measure. Finally, we describe a method for ranking multiword aspects by the likelihood of belonging to the target aspect category. The task used for evaluation is extraction of restaurant dish names from a corpus of restaurant reviews.
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- a
-
Ruge, G.; Schwarz, C.: Term association and computational linguistics (1991)
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- Abstract
- Most systems for term associations are statistically based. In general they exploit term co-occurrences. A critical overview about statistical approaches in this field is given. A new approach on the basis of a linguistic analysis for large amounts of textual data is outlined
- Type
- a
-
Kettunen, K.; Kunttu, T.; Järvelin, K.: To stem or lemmatize a highly inflectional language in a probabilistic IR environment? (2005)
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- Abstract
- Purpose - To show that stem generation compares well with lemmatization as a morphological tool for a highly inflectional language for IR purposes in a best-match retrieval system. Design/methodology/approach - Effects of three different morphological methods - lemmatization, stemming and stem production - for Finnish are compared in a probabilistic IR environment (INQUERY). Evaluation is done using a four-point relevance scale which is partitioned differently in different test settings. Findings - Results show that stem production, a lighter method than morphological lemmatization, compares well with lemmatization in a best-match IR environment. Differences in performance between stem production and lemmatization are small and they are not statistically significant in most of the tested settings. It is also shown that hitherto a rather neglected method of morphological processing for Finnish, stemming, performs reasonably well although the stemmer used - a Porter stemmer implementation - is far from optimal for a morphologically complex language like Finnish. In another series of tests, the effects of compound splitting and derivational expansion of queries are tested. Practical implications - Usefulness of morphological lemmatization and stem generation for IR purposes can be estimated with many factors. On the average P-R level they seem to behave very close to each other in a probabilistic IR system. Thus, the choice of the used method with highly inflectional languages needs to be estimated along other dimensions too. Originality/value - Results are achieved using Finnish as an example of a highly inflectional language. The results are of interest for anyone who is interested in processing of morphological variation of a highly inflected language for IR purposes.
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- a
-
Rettinger, A.; Schumilin, A.; Thoma, S.; Ell, B.: Learning a cross-lingual semantic representation of relations expressed in text (2015)
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Comeau, D.C.; Wilbur, W.J.: Non-Word Identification or Spell Checking Without a Dictionary (2004)
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- Abstract
- MEDLINE is a collection of more than 12 million references and abstracts covering recent life science literature. With its continued growth and cutting-edge terminology, spell-checking with a traditional lexicon based approach requires significant additional manual followup. In this work, an internal corpus based context quality rating a, frequency, and simple misspelling transformations are used to rank words from most likely to be misspellings to least likely. Eleven-point average precisions of 0.891 have been achieved within a class of 42,340 all alphabetic words having an a score less than 10. Our models predict that 16,274 or 38% of these words are misspellings. Based an test data, this result has a recall of 79% and a precision of 86%. In other words, spell checking can be done by statistics instead of with a dictionary. As an application we examine the time history of low a words in MEDLINE titles and abstracts.
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- a
-
Zhou, L.; Zhang, D.: NLPIR: a theoretical framework for applying Natural Language Processing to information retrieval (2003)
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- Abstract
- Zhou and Zhang believe that for the potential of natural language processing NLP to be reached in information retrieval a framework for guiding the effort should be in place. They provide a graphic model that identifies different levels of natural language processing effort during the query, document matching process. A direct matching approach uses little NLP, an expansion approach with thesauri, little more, but an extraction approach will often use a variety of NLP techniques, as well as statistical methods. A transformation approach which creates intermediate representations of documents and queries is a step higher in NLP usage, and a uniform approach, which relies on a body of knowledge beyond that of the documents and queries to provide inference and sense making prior to matching would require a maximum NPL effort.
- Type
- a
-
Driscoll, J.R.; Rajala, D.A.; Shaffer, W.H.: ¬The operation and performance of an artificially intelligent keywording system (1991)
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- Abstract
- Presents a new approach to text analysis for automating the key phrase indexing process, using artificial intelligence techniques. This mimics the behaviour of human experts by using a rule base consisting of insertion and deletion rules generated by subject-matter experts. The insertion rules are based on the idea that some phrases found in a text imply or trigger other phrases. The deletion rules apply to semantically ambiguous phrases where text presence alone does not determine appropriateness as a key phrase. The insertion and deletion rules are used to transform a list of found phrases to a list of key phrases for indexing a document. Statistical data are provided to demonstrate the performance of this expert rule based system
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- a
-
Haas, S.W.: ¬A feasibility study of the case hierarchy model for the construction and porting of natural language interfaces (1990)
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Sager, J.A.: ¬A practical course in terminology processing : with a bibliography by Blaise Nkwenti-Azeh (1990)
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-
Fellbaum, C.: ¬A semantic network of English : the mother of all WordNets (1998)
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Sharada, B.A.: Identification and interpretation of metaphors in document titles (1999)
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- Source
- Library science with a slant to documentation and information studies. 36(1999) no.1, S.27-33
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- a
