[PDF] Top 20 Identifying Events using Similarity and Context
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Identifying Events using Similarity and Context
... criteria, Similarity and InSeq, ...the Similarity criterion is disabled, any node that occurs in the proper order with the neighboring event can be added to the ... See full document
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Probabilistic models of similarity in syntactic context
... the similarity of the latent variable distributions associ- ated with seeing n and o in context ...that similarity between topic distributions corre- sponds to semantic similarity is ... See full document
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Mining Context Specific Similarity Relationships Using The World Wide Web
... a Context Specific Similarity Expansion (CSSE) technique based on word co-occurrence analysis within pages automatically harvested from the WWW (Web corpus) and performed extensive testing with a well known ... See full document
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Measuring Distributional Similarity in Context
... meaning similarity as operationalized by vector-based models has found widespread use in many tasks ranging from the acquisition of synonyms and para- phrases to word sense disambiguation and tex- tual ...word ... See full document
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Topic Models for Meaning Similarity in Context
... a context as we extract only patterns containing tar- get words together with their X and Y ...assign similarity scores to each candidate by comparing them to the pattern occurring in the original ... See full document
9
Context Feature Selection for Distributional Similarity
... for context selection in distribu- tional similarity, and our formalization of the prob- lem described in Section 2 turned out to be appro- priate for the ... See full document
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Finding Word Substitutions Using a Distributional Similarity Baseline and Immediate Context Overlap
... immediate context over- lap step dramatically increases our precision (from 41% to 56%), showing that a more stringent notion of similarity can be achieved when adequately fil- tering the output of a ... See full document
9
A Study on Word Similarity using Context Vector Models
... propose using only syntactic related co-occurrences as context vectors and adopt information theoretic models to solve the problems of data sparseness and characteristic ...co-occurrence context ... See full document
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Similarity of trajectories taking into account geographic context
... geographic context, most importantly the underlying land/sea structure, geographic latitude, surface temperature, and surface pressure ...of similarity analysis in movement research, this study aims at ... See full document
24
Context Based Similarity Analysis for Document Summarization
... a context-sensitive document indexing ...Sentence similarity is calculated using the context sensitive indexing where it should reflect the contextual similarity between two sentences ... See full document
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Probabilistic Modeling of Joint context in Distributional Similarity
... the context window order within the range of up to 4 words, our PDS model shows ...for context window orders larger than ...semantic similarity rather than ...to context words the farther away ... See full document
10
Context Based Semantic Similarity and Document Retrieval
... one context whereas it may mean a fruit or a tree in some other ...of context of terms is an issue in the field of lexical ...of similarity between has become a need of the hour for the building of ... See full document
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LMSim : Computing Domain specific Semantic Word Similarities Using a Language Modeling Approach
... words within the pairs Ricestar-Clincher 1 and sprangletop-Barnyardgrass 2 are semantically similar. In addition to text clustering, discovering semantically similar words has rich applications in the fields of ... See full document
6
Discriminating Among Word Senses Using McQuitty’s Similarity Analysis
... the context in which it oc- ...McQuitty’s Similarity Analysis, an agglomerative cluster- ing algorithm. The context in which a target word occurs is represented by surface lexical features such as ... See full document
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Querying Word Embeddings for Similarity and Relatedness
... for similarity and relatedness with a single vector representation for each word has led to the suggestion that distinct representations, and perhaps even distinct learn- ing models, are needed for optimal ... See full document
10
Handling Sparsity for Verb Noun MWE Token Classification
... the context vector of a VNC with the composed vector of the verb and noun (V-N) com- ponent units of the VNC when they occur in iso- lation of each other ...high similarity between the VNC and the com- ... See full document
8
Finding Synonyms Using Automatic Word Alignment and Measures of Distributional Similarity
... The alignment models produced are asymmet- ric and several heuristics exist to combine direc- tional word alignments to improve alignment ac- curacy. We believe, that precision is more cru- cial than recall in our ... See full document
8
Word Independent Context Pair Classification Model for Word Sense Disambiguation
... (2) LSA-based (Latent Semantic Analysis based) trigger word similarity: LSA (Deerwester et al. 1990) is a technique used to uncover the underlying semantics based on co-occurrence data. The first step of LSA is to ... See full document
7
Identifying Eyewitness News worthy Events on Twitter
... for identifying posts from eyewitnesses to various event types on Twitter, including shootings, police activ- ity, and ...semantic context has been pro- duced by the filter, eyewitness events can ... See full document
7
Identifying Prominent Arguments in Online Debates Using Semantic Textual Similarity
... Another observation concerns the level of argu- ment granularity. In the previous analysis, we used the gold number of clusters. We note, however, that the level of granularity is to a certain extent arbitrary. To ... See full document
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