semantic vector space model
Multiple Document Summarization Using Principal Component Analysis Incorporating Semantic Vector Space Model
... as Semantic Vector Space Model (SVSM) and applying Principal Component Analysis (PCA) to extract topic ...results. Vector space is enhanced semantically by modifying the weight ...
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A Systematic Study of Semantic Vector Space Model Parameters
... that semantic similarity studies have been overfit- ting to their idiosyncracies, so in this study we evaluate on a variety of datasets: in addition to WordSim353 (W353) and TOEFL, we also use the Rubenstein & ...
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Towards a Vector Space Model for FrameNet-like Resources
... to model FrameNet using minimal supervision, based on semantic ...to model the notion of ...the model to more sophisticated and application-oriented tasks, such as the induction of new LUs ...
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Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition
... We have performed a systematic study of comple- mentarity of topical (Document) and type (Depen- dency) features in Vector Space Model (VSM) for semantic composition of adjective-noun phrases. ...
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The Lifted Matrix Space Model for Semantic Composition
... to semantic composition gener- ally seen in formal linguistics, and have shown empirical improvements over comparable se- quence models by doing ...as model dimension or vocabulary size ...
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Measuring Word Relatedness Using Heterogeneous Vector Space Models
... the semantic relatedness of words is a fundamental problem in natural language process- ing and has many useful applications, including textual entailment, word sense disambiguation, in- formation retrieval and ...
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Feature2Vec: Distributional semantic modelling of human property knowledge
... high-dimensional semantic models to be constructed for a very large number of ...pretrained vector space model of word ...bedding space makes it possible to rank the rele- vance of ...
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Regular polysemy: from sense vectors to sense patterns
... like semantic shifts (lamb can denote either ANIMAL or FOOD), metonymy (church can denote either ORGANIZATION or LOCATION) and metaphor ...to model regular polysemy in semantic vector ...
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Automated Essay Scoring using Word2vec and Support Vector Machine
... word2vec model which converts words into features and synonyms in semantic space, Support Vector Machine(SVM) is used to classify students answers and estimate score ...
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Vector space calculation of semantic surprisal for predicting word pronunciation duration
... of semantic surprisal above ...between semantic surprisal and spoken word durations does not only hold for the semantic surprisal model, but also for the standard non-weight-adjusted in-domain ...
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On the Performance of Latent Semantic Indexing-based Information Retrieval
... format. Vector Space Model ( VSM ) is a conventional IR model, which repre- sents a document collection by a term-document ...dimensional space with inter document similarity measured ...
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Unsupervised Metaphor Paraphrasing using a Vector Space Model
... VS model produces a number of antonymous ...SP model which does not consider meaning retention, but rather the semantic fit of a candidate interpretation in the ...
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Evaluating vector space models using human semantic priming results
... Finally, it may be useful to experiment with other implicit cognitive measures known to reflect relation structure. A prominent example is the N400, a neural response elicited by every word during sentence comprehension ...
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Ontologically Grounded Multi sense Representation Learning for Semantic Vector Space Models
... single vector to every word, thus ignoring the possibility that words may have more than one ...to model multiple meanings is an important component of any NLP system, given how common polysemy is in ...
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A Structured Vector Space Model for Word Meaning in Context
... robust model of semantic similarity that has been used in NLP (Salton et ...to model experimental results in cognitive science (Landauer and Dumais, 1997; McDonald and Ramscar, ...2001). ...
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Performance Analysis of Layered Vector Space Model in Web Information Retrieval
... The point wise mutual information for information retrieval (PMI-IR) was suggested by Turney as an unsupervised measure for the evaluation of the semantic similarity of words. It is based on word co-occurrence ...
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Post hoc Manipulations of Vector Space Models with Application to Semantic Role Labeling
... explicitly model also ad- ditional information besides the semantic similar- ity between the predicate and the ...English vector space model was induced on a nearly four times larger ...
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A Vector Space Model for Subjectivity Classification in Urdu aided by Co Training
... This research provides interesting insights in modeling a subjectivity classifier for Urdu newswire data. We show that despite Urdu being a resource poor language, techniques like co- training and statistical techniques ...
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Lexical Transfer Using a Vector Space Model
... A bilingual dictionary consists of rules that map a part of the representation of a source sentence to a target representation by taking grammatical differences (such as the word order between the source and target ...
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Improving the relevancy of document search using the multi term adjacency keyword order model
... on vector space model. The proposed model focuses only on precision that favors to system which retrieves relevant documents quickly, that is early in the ...Classic vector space ...
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