... Figure 4: Compound noun disambiguation results We next conducted structural disambiguationon the test data, using the probabilities estimated based on 2D -Clustering and Brown. We also tested ... data. We hand-labeled the test data with the correct dis- ambiguation 'answers.' We performed clusteringon the nouns on the left position and the nouns on the right position in the ... the problem of clustering words (or con- structing a thesaurus) basedon co-occurrence data, and using the acquired word classes to improve the accuracy of syntactic disambiguation. We view this...
... featurereduction basedonwordclusteringand se-lection. A number of word similarity mea-sures are proposed for clustering words forthe Named Entity Recognition task. A fewcorpus based statistical ... important words for previous two and next two positions along with the suffix, prefix,digit and POS information.5.3 Relative Effectiveness of Clusteringand Word SelectionIn most of the cases clustering ... Important Word SelectionThe details of the comparison between the word fea-ture and the reduced features basedon important word selection are given in Table 6. For the sur-rounding word features,...
... fluctuation along withthe alteration of r.17Type FeaturesUnigram word i◦ posi word iposi word j◦ posj word jposjBigram word i◦ posi◦ word j◦ posjposi◦ word j◦ posj word i◦ word j◦ ... ourmodel and the transition -based category is thatthey all need a classifier to perform classificationconditioned on a certain configuration. However,they differ from each other in the classification ... for convenience. ACollins distance comprises the answers of 6 ques-tions:• Does word i precede or follow word j?• Are word i andword j adjacent?• Is there a verb between word i and word...
... limitedto align two languages only. The algorithm is veryflexible, and allows for straightforward explorationof different numbers and combinations of languages.6 Conclusion and Future WorkTranslating ... language and vice versa,which allows for disambiguation of phenomenawhich are ambiguous in only one of the languages.We use the above observations for cross-lingualparse disambiguation. We ... Computational Linguistics, pages 125–129,Jeju, Republic of Korea, 8-14 July 2012.c2012 Association for Computational LinguisticsCross-lingual Parse Disambiguationbasedon Semantic CorrespondenceLea...
... with j FL words and i Englishwords. For SU and SG, the majority of the phrasescontain only one FL word, and the percentage ofthe phrases with more than 2 FL words is less than18%. For the ... long-standing questions aboutthe value of alignment in the context of MT.We first evaluate 5 different word alignmentsintrinsically, using: (1) community-standardmetrics—precision, recall and ... were scored usingtranslation probabilities and lexical weights in twodirections and a phrase penalty score. We also usea language model, a distortion model and a word penalty feature for MT.We...
... Team, Information Services Division (ISD), NHS NationalServices, Scotland. Computing was done by Andrew Chan and Lee Young.none disclosed.Trendsin Cancer Survival in Scotland 1971-1995REFERENCES1Goldacre ... and abortion:collaborative reanalysis of data from 53 epidemiological studies.2004;363:1007-1016.Erlandsson G, Montgomery SM, Cnattingius S, Ekborn A. Abortions and breast cancer: record based ... for Republic of Ireland;2004 for England & Wales, Scotland, Northern Ireland, and Sweden; 2003 for Czech Republic and Finland; 2001 for Denmark).Linear Regression. Response variable: cumulated...
... modificand relation. Experiment Disambiguation of dependency re- lations was done using 75 anlbiguous con- structions from Fukumoto (1992). Solving the ambiguity in the constructions involves ... experiment on the data that consists of all the 21,046 semantically annotated verb-noun- preposition-noun constructions found in EDR English Corpus. We set aside 500 constructions for test and ... identifica- tion of a reliable and specific class for each co- occurrence in consideration and can deal with date sparseness problem more efficiently. It 1421 Structural DisambiguationBasedon Reliable...
... All-optical NAND andAND Gates basedon 3x3 GI-MMI couplers Theory: The conventional MMI coupler has a structure consisting of a homogeneous planar multimode waveguide region connected to a ... AND, NOT and NOR gates in waveguides consisting of nonlinear material, IEICE Transactions on Electronics, vol. E83-C (2000) 1755. [7] W. Youfa, L. Jianhua, All-fiber logical devices basedon ... order to obtain a nonlinear interaction. In addition, since the nonlinear coefficient is often small, long interaction lengths are generally required. Moreover, devices basedon nonlinear effects...
... classification I Figure 1: 5WIH classification and navigation 3 5WIH Classification and Navigation Conventional keyword -based retrieval does not con- sider logical relationships between keywords. ... information on the lattice produced by the existence of keywords (Carpineto and Romano, 1995). 5WlH classification and navigation is unique in that it is basedon keyword functions, not on the ... understand intuitively. The clusters have no logical meaning because they depend on a keyword set basedon the frequency that keywords occur. Scatter/Gather is clustering information based on...
... not for citation purposes)Journal of Translational MedicineOpen AccessResearchA comparison of classification methods for predicting Chronic Fatigue Syndrome basedon genetic data Lung-Cheng ... the complex relationship betweenCFS and SNPs.Conclusion: We demonstrated that our approach is a promising method to assess theassociations between CFS and SNPs.BackgroundChronic fatigue syndrome ... tested responders, and specificity, the proportion of correctly predicted non-responders of all the tested non-responders.To investigate the generalization of the prediction modelsproduced...
... biggest S(c).3 Test dataand evaluation methodsThe proposed method was tested on the dis-tributional dataon nouns obtained from two cor-pora: the British National Corpus (BNC) and theAssociated ... relativeimprovement).ReferencesE.Alfonseca and S.Manandhar. 2002. Extending aLexical Ontology by a Combination of Distribu-tional Semantics Signatures. Proceedings ofEKAW-2002:1-7.A.Budanitsky and G.Hirst. 2001. ... distance inWordNet: An experimental, application-orientedevaluation of five measures. Proceedings of NorthAmerican Chapter of ACL Workshop on WordNet and Other Lexical Resources.U.Hahn and K.Schattinger....
... collocations using similarity- based estimation. Next, we present a clustering method and a method for verbal word sense dis- ambiguation using the result of clustering. Fi- nally, we report on ... the data we used in our experiment. 8 Conclusion In this study, we proposed a method for disam- biguating verbal word senses using term weight learning basedon similarity -based estimation. ... her/his intuition, how many senses a word has, and then identify the sets of co-occurring words that correspond to the different senses. 213 Proceedings of EACL '99 and the synonymy of take...
... P., R. Ilson, J. Ayto, et al. (1978), Longman Dictionary of Contemporary English, Longman, Harlow and London. Salton, G. (1989) Automatic Text Processing, Addison-Wesley. Shipstone, E. (1960) ... (Mosteller and Wallace, 1964, section 3.1) and information retrieval (IR) (van Rijsbergen, 1979, chapter 6; Salton, 1989, section 10.3), though their application to word- sense disambiguation is ... large. I. It is common to use very small contexts (e.g., 5-words) basedon the observation that people seem to be able to disambiguate word- senses basedon very little context. We have taken...
... combinations of literal paraphrases whichonly consist of nouns and nonliteral paraphraseswhich only consist of verbs.6 ConclusionWe propose three models for sense disambigua-tion on words and ... distribution and sampling a word from thattopic, the enhanced model also generates a distri-butional neighbour for the chosen wordand thenassigns a sense basedon the word, its neighbour and the ... the con-ditional word- document probability distributionp(w|d) into two different distributions: the word- topic distribution p(w|z), and the topic-documentdistribution p(z|d) (see Equation 1)....