Search (25 results, page 1 of 2)

  • × year_i:[2000 TO 2010}
  • × theme_ss:"Computerlinguistik"
  1. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.11 
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    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
  2. He, Q.: ¬A study of the strength indexes in co-word analysis (2000) 0.03 
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    Abstract
    Co-word analysis is a technique for detecting the knowledge structure of scientific literature and mapping the dynamics in a research field. It is used to count the co-occurrences of term pairs, compute the strength between term pairs, and map the research field by inserting terms and their linkages into a graphical structure according to the strength values. In previous co-word studies, there are two indexes used to measure the strength between term pairs in order to identify the major areas in a research field - the inclusion index (I) and the equivalence index (E). This study will conduct two co-word analysis experiments using the two indexes, respectively, and compare the results from the two experiments. The results show, due to the difference in their computation, index I is more likely to identify general subject areas in a research field while index E is more likely to identify subject areas at more specific levels
  3. Vilares, J.; Alonso, M.A.; Vilares, M.: Extraction of complex index terms in non-English IR : a shallow parsing based approach (2008) 0.02 
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    Abstract
    The performance of information retrieval systems is limited by the linguistic variation present in natural language texts. Word-level natural language processing techniques have been shown to be useful in reducing this variation. In this article, we summarize our work on the extension of these techniques for dealing with phrase-level variation in European languages, taking Spanish as a case in point. We propose the use of syntactic dependencies as complex index terms in an attempt to solve the problems deriving from both syntactic and morpho-syntactic variation and, in this way, to obtain more precise index terms. Such dependencies are obtained through a shallow parser based on cascades of finite-state transducers in order to reduce as far as possible the overhead due to this parsing process. The use of different sources of syntactic information, queries or documents, has been also studied, as has the restriction of the dependencies applied to those obtained from noun phrases. Our approaches have been tested using the CLEF corpus, obtaining consistent improvements with regard to classical word-level non-linguistic techniques. Results show, on the one hand, that syntactic information extracted from documents is more useful than that from queries. On the other hand, it has been demonstrated that by restricting dependencies to those corresponding to noun phrases, important reductions of storage and management costs can be achieved, albeit at the expense of a slight reduction in performance.
  4. Witschel, H.F.: Terminology extraction and automatic indexing : comparison and qualitative evaluation of methods (2005) 0.02 
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    Abstract
    Many terminology engineering processes involve the task of automatic terminology extraction: before the terminology of a given domain can be modelled, organised or standardised, important concepts (or terms) of this domain have to be identified and fed into terminological databases. These serve in further steps as a starting point for compiling dictionaries, thesauri or maybe even terminological ontologies for the domain. For the extraction of the initial concepts, extraction methods are needed that operate on specialised language texts. On the other hand, many machine learning or information retrieval applications require automatic indexing techniques. In Machine Learning applications concerned with the automatic clustering or classification of texts, often feature vectors are needed that describe the contents of a given text briefly but meaningfully. These feature vectors typically consist of a fairly small set of index terms together with weights indicating their importance. Short but meaningful descriptions of document contents as provided by good index terms are also useful to humans: some knowledge management applications (e.g. topic maps) use them as a set of basic concepts (topics). The author believes that the tasks of terminology extraction and automatic indexing have much in common and can thus benefit from the same set of basic algorithms. It is the goal of this paper to outline some methods that may be used in both contexts, but also to find the discriminating factors between the two tasks that call for the variation of parameters or application of different techniques. The discussion of these methods will be based on statistical, syntactical and especially morphological properties of (index) terms. The paper is concluded by the presentation of some qualitative and quantitative results comparing statistical and morphological methods.
  5. Pirkola, A.: Morphological typology of languages for IR (2001) 0.02 
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    Abstract
    This paper presents a morphological classification of languages from the IR perspective. Linguistic typology research has shown that the morphological complexity of every language in the world can be described by two variables, index of synthesis and index of fusion. These variables provide a theoretical basis for IR research handling morphological issues. A common theoretical framework is needed in particular because of the increasing significance of cross-language retrieval research and CLIR systems processing different languages. The paper elaborates the linguistic morphological typology for the purposes of IR research. It studies how the indexes of synthesis and fusion could be used as practical tools in mono- and cross-lingual IR research. The need for semantic and syntactic typologies is discussed. The paper also reviews studies made in different languages on the effects of morphology and stemming in IR.
  6. Airio, E.; Kettunen, K.: Does dictionary based bilingual retrieval work in a non-normalized index? (2009) 0.02 
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    Abstract
    Many operational IR indexes are non-normalized, i.e. no lemmatization or stemming techniques, etc. have been employed in indexing. This poses a challenge for dictionary-based cross-language retrieval (CLIR), because translations are mostly lemmas. In this study, we face the challenge of dictionary-based CLIR in a non-normalized index. We test two optional approaches: FCG (Frequent Case Generation) and s-gramming. The idea of FCG is to automatically generate the most frequent inflected forms for a given lemma. FCG has been tested in monolingual retrieval and has been shown to be a good method for inflected retrieval, especially for highly inflected languages. S-gramming is an approximate string matching technique (an extension of n-gramming). The language pairs in our tests were English-Finnish, English-Swedish, Swedish-Finnish and Finnish-Swedish. Both our approaches performed quite well, but the results varied depending on the language pair. S-gramming and FCG performed quite equally in all the other language pairs except Finnish-Swedish, where s-gramming outperformed FCG.
  7. Boleda, G.; Evert, S.: Multiword expressions : a pain in the neck of lexical semantics (2009) 0.02 
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    Date
    1. 3.2013 14:56:22
  8. Monnerjahn, P.: Vorsprung ohne Technik : Übersetzen: Computer und Qualität (2000) 0.02 
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    Source
    c't. 2000, H.22, S.230-231
  9. Li, Q.; Chen, Y.P.; Myaeng, S.-H.; Jin, Y.; Kang, B.-Y.: Concept unification of terms in different languages via web mining for Information Retrieval (2009) 0.02 
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    Abstract
    For historical and cultural reasons, English phrases, especially proper nouns and new words, frequently appear in Web pages written primarily in East Asian languages such as Chinese, Korean, and Japanese. Although such English terms and their equivalences in these East Asian languages refer to the same concept, they are often erroneously treated as independent index units in traditional Information Retrieval (IR). This paper describes the degree to which the problem arises in IR and proposes a novel technique to solve it. Our method first extracts English terms from native Web documents in an East Asian language, and then unifies the extracted terms and their equivalences in the native language as one index unit. For Cross-Language Information Retrieval (CLIR), one of the major hindrances to achieving retrieval performance at the level of Mono-Lingual Information Retrieval (MLIR) is the translation of terms in search queries which can not be found in a bilingual dictionary. The Web mining approach proposed in this paper for concept unification of terms in different languages can also be applied to solve this well-known challenge in CLIR. Experimental results based on NTCIR and KT-Set test collections show that the high translation precision of our approach greatly improves performance of both Mono-Lingual and Cross-Language Information Retrieval.
  10. Kuhlmann, U.; Monnerjahn, P.: Sprache auf Knopfdruck : Sieben automatische Übersetzungsprogramme im Test (2000) 0.01 
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    Source
    c't. 2000, H.22, S.220-229
  11. Herrera-Viedma, E.: Modeling the retrieval process for an information retrieval system using an ordinal fuzzy linguistic approach (2001) 0.01 
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    Abstract
    A linguistic model for an Information Retrieval System (IRS) defined using an ordinal fuzzy linguistic approach is proposed. The ordinal fuzzy linguistic approach is presented, and its use for modeling the imprecision and subjectivity that appear in the user-IRS interaction is studied. The user queries and IRS responses are modeled linguistically using the concept of fuzzy linguistic variables. The system accepts Boolean queries whose terms can be weighted simultaneously by means of ordinal linguistic values according to three possible semantics: a symmetrical threshold semantic, a quantitative semantic, and an importance semantic. The first one identifies a new threshold semantic used to express qualitative restrictions on the documents retrieved for a given term. It is monotone increasing in index term weight for the threshold values that are on the right of the mid-value, and decreasing for the threshold values that are on the left of the mid-value. The second one is a new semantic proposal introduced to express quantitative restrictions on the documents retrieved for a term, i.e., restrictions on the number of documents that must be retrieved containing that term. The last one is the usual semantic of relative importance that has an effect when the term is in a Boolean expression. A bottom-up evaluation mechanism of queries is presented that coherently integrates the use of the three semantics and satisfies the separability property. The advantage of this IRS with respect to others is that users can express linguistically different semantic restrictions on the desired documents simultaneously, incorporating more flexibility in the user-IRS interaction
  12. Bellaachia, A.; Amor-Tijani, G.: Proper nouns in English-Arabic cross language information retrieval (2008) 0.01 
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    Abstract
    Out of vocabulary words, mostly proper nouns and technical terms, are one main source of performance degradation in Cross Language Information Retrieval (CLIR) systems. Those are words not found in the dictionary. Bilingual dictionaries in general do not cover most proper nouns, which are usually primary keys in the query. As they are spelling variants of each other in most languages, using an approximate string matching technique against the target database index is the common approach taken to find the target language correspondents of the original query key. N-gram technique proved to be the most effective among other string matching techniques. The issue arises when the languages dealt with have different alphabets. Transliteration is then applied based on phonetic similarities between the languages involved. In this study, both transliteration and the n-gram technique are combined to generate possible transliterations in an English-Arabic CLIR system. We refer to this technique as Transliteration N-Gram (TNG). We further enhance TNG by applying Part Of Speech disambiguation on the set of transliterations so that words with a similar spelling, but a different meaning, are excluded. Experimental results show that TNG gives promising results, and enhanced TNG further improves performance.
  13. Doszkocs, T.E.; Zamora, A.: Dictionary services and spelling aids for Web searching (2004) 0.01 
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    Date
    14. 8.2004 17:22:56
    Source
    Online. 28(2004) no.3, S.22-29
  14. Hammwöhner, R.: TransRouter revisited : Decision support in the routing of translation projects (2000) 0.01 
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    Date
    10.12.2000 18:22:35
  15. Schneider, J.W.; Borlund, P.: ¬A bibliometric-based semiautomatic approach to identification of candidate thesaurus terms : parsing and filtering of noun phrases from citation contexts (2005) 0.01 
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    Date
    8. 3.2007 19:55:22
  16. Paolillo, J.C.: Linguistics and the information sciences (2009) 0.01 
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    Date
    27. 8.2011 14:22:33
  17. Schneider, R.: Web 3.0 ante portas? : Integration von Social Web und Semantic Web (2008) 0.01 
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    22. 1.2011 10:38:28
  18. Bian, G.-W.; Chen, H.-H.: Cross-language information access to multilingual collections on the Internet (2000) 0.01 
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    16. 2.2000 14:22:39
  19. Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006) 0.01 
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    Date
    22. 3.2015 9:17:30
  20. Sienel, J.; Weiss, M.; Laube, M.: Sprachtechnologien für die Informationsgesellschaft des 21. Jahrhunderts (2000) 0.01 
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    Date
    26.12.2000 13:22:17

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