[PDF] Top 20 A General Framework for Distributional Similarity
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A General Framework for Distributional Similarity
... high freq, sim mi.. low freq, sim mi.[r] ... See full document
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Reducing Semantic Drift with Bagging and Distributional Similarity
... Iterative bootstrapping algorithms have been pro- posed to extract semantic lexicons for NLP tasks with limited linguistic resources. Bootstrapping was initially proposed by Riloff and Jones (1999), and has since been ... See full document
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Feature Vector Quality and Distributional Similarity
... too general (destination, ambition), and hence not indicative and may co-occur with many different types of ...high similarity scores for less simi- lar word pairs, while missing other correct similari- ... See full document
7
Characterising Measures of Lexical Distributional Similarity
... of distributional generality in- troduced in the previous section has parallels with the linguistic relation of hyponymy, where a hypernym is a semantically more general term and a hyponym is a semantically ... See full document
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Discriminative Improvements to Distributional Sentence Similarity
... a distributional representation for the entire ...LSA framework, and identify paraphrases using similarity in the la- tent ...ual distributional features and (2) learn the impor- tance of each ... See full document
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Sketch Techniques for Scaling Distributional Similarity to the Web
... efficient framework to scale dis- tributional similarity to the ...semantic similarity between word pairs in O(K) time and can compute similarity between any word pairs that are stored in the ... See full document
6
Matching the Blanks: Distributional Similarity for Relation Learning
... build general purpose extractors that represent relations with their surface forms, or which jointly embed surface forms with rela- tions from an existing knowledge ...Harris’ distributional hypothesis to ... See full document
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Combining Supervised and Unsupervised Parsing for Distributional Similarity
... of distributional thesauri, and comparing words along their syntactic contexts does rely on the existence of such a structure rather than its actual representation, we believe that distribu- tional similarities ... See full document
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Scaling Distributional Similarity to Large Corpora
... a general property of Machine Learning that increasing the volume of training data increases the accuracy of ...using distributional similarity produces continuing gains in accuracy as the volume of ... See full document
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Probabilistic Modeling of Joint context in Distributional Similarity
... traditional distributional similarity models fail to capture syntagmatic patterns that group together multiple word features within the same joint ...generic distributional similarity scheme ... See full document
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Detect Overlapping Community With Reliability Measure And Rule Based For Improving Recommender Systems
... The general framework of the proposed recommender algorithm including three steps, (i) a method to detect overlapping communities with using the similarity matrix between users, (ii) time based ... See full document
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Predicting the relevance of distributional semantic similarity with contextual information
... Using distributional analysis methods to compute semantic proximity links be- tween words has become commonplace in ...a distributional resource and filter- ing the relations it contains, but instead of ... See full document
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Hypernym Discovery Based on Distributional Similarity and Hierarchical Structures
... covered new patterns by which to semi- automatically extract hyponymy relations. Pantel et al. (2004a) proposed a method to automatical- ly discover the patterns using a minimal edit dis- tance. Ando et al. (2003) ... See full document
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Web Scale Distributional Similarity and Entity Set Expansion
... term similarity (Pantel and Lin 2002) to find term clusters (in an open extraction ...tributional similarity to find terms similar to the seed set (Paşca’s work also examines the advan- tages of combining ... See full document
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JoBimText Visualizer: A Graph based Approach to Contextualizing Distributional Similarity
... the framework flexible and abstract with re- spect to the pre-processing that identifies structure in language material, we introduce the holing op- eration, ...more general than similar formulations found ... See full document
5
Measuring Distributional Similarity in Context
... Word Similarity Our results on word similar- ity are summarized in Table 2. The simple co- occurrence based vector space (SVS) performed best with tf-idf weighting and the cosine similarity mea- sure. With ... See full document
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Distributional Memory: A General Framework for Corpus Based Semantics
... of distributional data as weighted triples is more akin to other standard knowledge representation formats based on typed relations, which are familiar to most computer and cognitive ...a general-purpose ... See full document
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Co occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity
... over distributional classes can similarly be disputed (Weeds ...Finally, distributional classes may be over-fitted to a specific corpus, but this may be beneficial to the extent that the over-fitting ... See full document
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From Global to Local Similarities: A Graph Based Contextualization Method using Distributional Thesauri
... graph-based framework for term similarity, we introduce a new con- textualization method that generates, for each term occurrence in a text, a ranked list of terms that are semantically similar and ... See full document
5
Distributional Similarity Models: Clustering vs Nearest Neighbors
... Second, each has a single free parameter k, and the two k's enjoy a natural inverse correspondence: a large number of clusters in the distributional clustering case results in only the c[r] ... See full document
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