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Babik, W.: Keywords as linguistic tools in information and knowledge organization (2017)
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- Language
- e
- Source
- Theorie, Semantik und Organisation von Wissen: Proceedings der 13. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und dem 13. Internationalen Symposium der Informationswissenschaft der Higher Education Association for Information Science (HI) Potsdam (19.-20.03.2013): 'Theory, Information and Organization of Knowledge' / Proceedings der 14. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und Natural Language & Information Systems (NLDB) Passau (16.06.2015): 'Lexical Resources for Knowledge Organization' / Proceedings des Workshops der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) auf der SEMANTICS Leipzig (1.09.2014): 'Knowledge Organization and Semantic Web' / Proceedings des Workshops der Polnischen und Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) Cottbus (29.-30.09.2011): 'Economics of Knowledge Production and Organization'. Hrsg. von W. Babik, H.P. Ohly u. K. Weber
-
Kocijan, K.: Visualizing natural language resources (2015)
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- Language
- e
- Source
- Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
-
Järvelin, A.; Keskustalo, H.; Sormunen, E.; Saastamoinen, M.; Kettunen, K.: Information retrieval from historical newspaper collections in highly inflectional languages : a query expansion approach (2016)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Clark, M.; Kim, Y.; Kruschwitz, U.; Song, D.; Albakour, D.; Dignum, S.; Beresi, U.C.; Fasli, M.; Roeck, A De: Automatically structuring domain knowledge from text : an overview of current research (2012)
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- Date
- 29. 1.2016 18:29:51
- Language
- e
-
Schöneberg, U.; Sperber, W.: POS tagging and its applications for mathematics (2014)
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- Date
- 29. 3.2015 19:34:37
- Language
- e
-
Vlachidis, A.; Binding, C.; Tudhope, D.; May, K.: Excavating grey literature : a case study on the rich indexing of archaeological documents via natural language-processing techniques and knowledge-based resources (2010)
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- Date
- 29. 8.2010 12:03:40
- Language
- e
-
Bowker, L.; Ciro, J.B.: Machine translation and global research : towards improved machine translation literacy in the scholarly community (2019)
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- Classification
- BFP (FH K)
- Footnote
- Rez. in: JASIST 71(2020) no.10, S.1275-1278 (Krystyna K. Matusiak).
- GHBS
- BFP (FH K)
- Language
- e
-
Al-Shawakfa, E.; Al-Badarneh, A.; Shatnawi, S.; Al-Rabab'ah, K.; Bani-Ismail, B.: ¬A comparison study of some Arabic root finding algorithms (2010)
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- Language
- e
-
Colace, F.; Santo, M. De; Greco, L.; Napoletano, P.: Weighted word pairs for query expansion (2015)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Moohebat, M.; Raj, R.G.; Kareem, S.B.A.; Thorleuchter, D.: Identifying ISI-indexed articles by their lexical usage : a text analysis approach (2015)
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- Abstract
- This research creates an architecture for investigating the existence of probable lexical divergences between articles, categorized as Institute for Scientific Information (ISI) and non-ISI, and consequently, if such a difference is discovered, to propose the best available classification method. Based on a collection of ISI- and non-ISI-indexed articles in the areas of business and computer science, three classification models are trained. A sensitivity analysis is applied to demonstrate the impact of words in different syntactical forms on the classification decision. The results demonstrate that the lexical domains of ISI and non-ISI articles are distinguishable by machine learning techniques. Our findings indicate that the support vector machine identifies ISI-indexed articles in both disciplines with higher precision than do the Naïve Bayesian and K-Nearest Neighbors techniques.
- Language
- e
-
Lu, K.; Cai, X.; Ajiferuke, I.; Wolfram, D.: Vocabulary size and its effect on topic representation (2017)
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- Language
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Ramisch, C.: Multiword expressions acquisition : a generic and open framework (2015)
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- Classification
- BFP (FH K)
- GHBS
- BFP (FH K)
- Language
- e
-
Li, N.; Sun, J.: Improving Chinese term association from the linguistic perspective (2017)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Hahn, U.: Methodische Grundlagen der Informationslinguistik (2013)
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- Source
- Grundlagen der praktischen Information und Dokumentation. Handbuch zur Einführung in die Informationswissenschaft und -praxis. 6., völlig neu gefaßte Ausgabe. Hrsg. von R. Kuhlen, W. Semar u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried
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Sankarasubramaniam, Y.; Ramanathan, K.; Ghosh, S.: Text summarization using Wikipedia (2014)
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- Language
- e
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Savoy, J.: Text representation strategies : an example with the State of the union addresses (2016)
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- Abstract
- Based on State of the Union addresses from 1790 to 2014 (225 speeches delivered by 42 presidents), this paper describes and evaluates different text representation strategies. To determine the most important words of a given text, the term frequencies (tf) or the tf?idf weighting scheme can be applied. Recently, latent Dirichlet allocation (LDA) has been proposed to define the topics included in a corpus. As another strategy, this study proposes to apply a vocabulary specificity measure (Z?score) to determine the most significantly overused word-types or short sequences of them. Our experiments show that the simple term frequency measure is not able to discriminate between specific terms associated with a document or a set of texts. Using the tf idf or LDA approach, the selection requires some arbitrary decisions. Based on the term-specific measure (Z?score), the term selection has a clear theoretical basis. Moreover, the most significant sentences for each presidency can be determined. As another facet, we can visualize the dynamic evolution of usage of some terms associated with their specificity measures. Finally, this technique can be employed to define the most important lexical leaders introducing terms overused by the k following presidencies.
- Language
- e
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Lian, T.; Yu, C.; Wang, W.; Yuan, Q.; Hou, Z.: Doctoral dissertations on tourism in China : a co-word analysis (2016)
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- Abstract
- The aim of this paper is to map the foci of research in doctoral dissertations on tourism in China. In the paper, coword analysis is applied, with keywords coming from six public dissertation databases, i.e. CDFD, Wanfang Data, NLC, CALIS, ISTIC, and NSTL, as well as some university libraries providing doctoral dissertations on tourism. Altogether we have examined 928 doctoral dissertations on tourism written between 1989 and 2013. Doctoral dissertations on tourism in China involve 36 first level disciplines and 102 secondary level disciplines. We collect the top 68 keywords of practical significance in tourism which are mentioned at least four times or more. These keywords are classified into 12 categories based on co-word analysis, including cluster analysis, strategic diagrams analysis, and social network analysis. According to the strategic diagram of the 12 categories, we find the mature and immature areas in tourism study. From social networks, we can see the social network maps of original co-occurrence matrix and k-cores analysis of binary matrix. The paper provides valuable insight into the study of tourism by analyzing doctoral dissertations on tourism in China.
- Language
- e
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Lhadj, L.S.; Boughanem, M.; Amrouche, K.: Enhancing information retrieval through concept-based language modeling and semantic smoothing (2016)
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K., Vani; Gupta, D.: Unmasking text plagiarism using syntactic-semantic based natural language processing techniques : comparisons, analysis and challenges (2018)
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Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
