... Cambridge, MA. 450 Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line Line 1234567890123456789012345678901234567890123456789012345678901234567890 ... Computational Lin- guistics, pages 19-24. Shona Douglas, Matthew Hurst, and David Quinn. 1995. Using natural language processing for iden- tifying and interpreting tablesin plain text. In Fourth ... blank lines or delimiters that immediately precede or follow a table within an input text. In this paper, we assume that our input texts are plain texts that do not contain any formatting codes,...
... System; using System.Configuration; using System .Text; using System.Data; using System.Data.OleDb; // . . . // OLE DB StringBuilder result = new StringBuilder( ); // Open the OLE DB ... ConfigurationSettings.AppSettings["MsAccess_ConnectString"]); conn.Open( ); // Retrieve schema information for all tables. DataTable schemaTable = conn.GetOleDbSchemaTable(OleDbSchemaGuid .Tables, ... [ Team LiB ] Recipe 10.14 Listing Tablesin an Access Database Problem You need a list of all tablesin your Access database. Solution Use the GetOLEDBSchemaTable(...
... previously seen in the training corpus,and therefore their overall coverage is not 100%.Starting with an annotated corpus consisting of allannotated files in SemCor, a separate training data setis ... Min-imally supervised word sense disambiguation for allwords in open text. In Proceedings of ACL/SIGLEXSenseval-3, Barcelona, Spain, July.R. Mihalcea and D. Moldovan. 2002. Pattern learningand ... vectors constructed in this learn-ing stage for each semantic model.To annotate new text, similar vectors are created forall content-words in the raw text. Similar to the train-ing stage, feature...
... 2000.Mapping wordnets using structural information. In Proceedings of the 38th Annual Meeting of theAssociation for Computational Linguistics, HongKong.Finding Predominant Word Senses in Untagged Text Diana ... BNC text represents imaginative writing, the remaining80% being classified as informative.sense according to SemCor. This seems intuitivegiven our expected relative usage of these senses in modern ... word sense disam-biguation using WordNet. In Proceedings ofthe Third International Conference on Intelligent Text Processing and Computational Linguistics(CICLing-02), Mexico City.Edward Briscoe...
... Vector Space Model (VSM) intext information processing, document indexing (term extraction) acts as a pre-requisite step in most text information proc-essing tasks such as Information Retrieval ... Intelligent Text Processing (CI-CLing 2003), 602-614. Yuan Liu, Nanyuan Liang. 1986. Basic Engineering for Chinese Processing – Contemporary Chinese Words Frequency Count, Journal of Chinese In- formation ... Xiaojing Bai, Shiwen Yu. 2003. Experimental Study on Representing Units in Chinese Text Categorization, Proceedings of the 4th International Conference on Computational Linguistics and Intelligent...
... principles of reasoning with uncertainty: e.g. Connoly (1994) and Mitkov (1997). Our system can be included into the first approach. In these integrated approaches the semantic and domain ... worked on different texts (Spanish texts). apply a partial parsing and we deal with other kinds of anaphors. As a future aim we will include semantic information in our algorithm in order to check ... which includes all the coordinated noun phrases (in this case John and Bill). We will detect the coordination of noun phrases from the SS returned by the SUG fact coordinated. In one- 4 In...
... manipulation of the evolving text structure, including the insertion of text structure nodes, grammatical marking of the nodes, textual ordering, and clause combin- ing. Currently, the network ... the ter- minating condition). Finally, they may or may not be combined into a single sentence with the ex- pression of their related action (the issue of clause combining). Text generation ... proven useful in analyzing various kinds of conditions and circumstances that fre- quently arise in instructions. The analysis involves addressing two related issues: 1. Determining the range...
... Distinguishing word senses in untagged text. In Proc. of the 2nd Conference on Empirical Methods in Natu- ral Language Processing, pages 197-207. H. Schutze. 1992. Dimensions of meaning. In ... methods. In Proc. of the 33rd Annual Meeting of the ACL, pages 189-196. U. Zernik. 1991. Trainl vs. train2: Tagging word senses in corpus. In Lexical acquisi- tion: Exploiting on-line resources ... unsupervised learning al- gorithm for disambiguating verbal word senses us- ing term weight learning. In our approach, an overlapping clustering algorithm based on Mutual information-based...
... features of the text that convey a definite meaning; encyclopedic rules, which can evaluate importance by comparing the meaning of the text with domain specific knowledge contained in the encyclopedia. ... structure: it is a logical con~)ination of key-terms, chosen in a predefinite set, that represent possible points of view a reader can take in analyzing a text. In this section we will illustrate ... operation, and discusses some meaningful examples. I. INTRODUCTION Text understanding has received increasing attention in recent years. A major problem in this area is that of importance...
... pronoun is le, third person feminine singular. 2 ° L1 contains the tokens which appear in the left-hand context that have been synthesized as feminine singular nominal phrases, i.e. L1 = (MISS ... (elided form of the masculine singular lo or of the feminine singular la ) does not indicate the gender of its antecedent. However, this gender is marked in the feminine past participle abbandonata ... distinguished. - 228 - semantic information. Let us consider the following definition of the token TABLI: TABL1 : TABLE NUMBER: 1 DEFINITE: yes It can be synthesized as a feminine nominal...
... already in- 1023Query No. User input1 something inhibit ERK22 something trigger diabetes3 adiponectin increase something4 TNF activate IL65 dystrophin cause disease6 macrophage induce something7 ... an ancestor of B. In [tag] Region covered with “<tag>”A > B A containing BA >> B A containing B (A is not nested)A < B A contained by BA << B A contained by B (B is ... is significantly improved.1 IntroductionRapid expansion of text information has motivatedthe development of efficient methods of access-ing information in huge texts. Furthermore, userdemand...
... Thedescent of hierarchy, and selection in relational se-mantics. Proceedings of ACL-02.P. Srinivasan and T. Rindflesch. 2002. Exploring text mining from Medline. Proceedings of the AMIASymposium.C. ... informationextraction. Proceedings of IJCAI-2001.T. Rindflesch, L. Hunter, and L. Aronson. 1999. Min-ing molecular binding terminology from biomedical text. Proceedings of the AMIA Symposium.B. ... AAAI-99 Workshop on Machine Learningfor Information Extraction.R. Feldman, Y. Regev, M. Finkelstein-Landau,E. Hurvitz, and B. Kogan. 2002. Mining biomed-ical literature using information extraction....