Semantic Clustering
Spatio Temporal Analysis of Moving Objects in Supply Chain Networks using Semantic Clustering
... If multiple trajectories of freight movement are analyzed using the semantic clustering system, it will provide the potential stops. The stops identified from various trajectories implies areas where the ...
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Semantic Clustering: an Attempt to Identify Multiword Expressions in Bengali
... Semantic clustering aims to cluster semantically related tokens present in a document. Identifying semantically related words for a particular token is carried out by looking the surrounding tokens and ...
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Semantic Clustering and Convolutional Neural Network for Short Text Categorization
... on semantic clustering and convolutional neural ...discover semantic cliques in embedding spaces by a fast clustering ...multi-scale semantic u- nits are detected under the supervision ...
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Using Semantic Clustering for Detecting Bengali Multiword Expressions
... of semantic similarity between two constituents of a candidate bigram indicates the less probability of the candidate to be a multiword ...the semantic clustering approach outperforms the other ...
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Learning Kernels for Semantic Clustering: A Deep Approach
... At the moment, our theoretical framework analyzes semantic embedding in the sense of a criterion for semantic clustering. However, correspondences be- tween linguistic intuitions and the showed ...
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Knowledge based Semantic Clustering
... in semantic overlay networks [11, 15, ...peer clustering. Used in this way, peer clustering introduces a hierarchy of peer groups based on ...on semantic closeness, recorded performance, ...
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SEMANTIC CLUSTERING WITH CONTEXT ONTOLOGY FOR INFORMATION RETRIEVAL SYSTEM
... Nowadays, there are so many increasing amount of information within world-wide web. For these increasing amounts of information, we need efficient and effective index structure when we have to find needed information. ...
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Domain Adaptable Semantic Clustering in Statistical NLG
... the semantic structure of a given domain of discourse which is then used to produce templates for our system (combining the Micro Planning and Surface Realization ...underlying semantic structures (Galley ...
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Fuzzy K-means Application to Semantic Clustering for Image Retrieval
... K-means clustering algorithm to analyze the academic performances of students on the basis of some pre set measures and the Euclidean distance as a measure of similarity distance which provide a simple and ...
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Semantic Clustering of Pivot Paraphrases
... Table 1 contains the evaluation results. Our clusters, es- pecially the coarse-grained ones (components), outperform the 1c1par baseline on both paired F-Score and V-measure. This shows that the clusters encode correct ...
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Design and Develop Semantic Textual Document Clustering Model
... valuable clustering on textual documents for grab the secret information from unsupervised, unclassified ...the semantic meaning of textual ...the semantic value of data and maintain relation ...
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A Review On Specification Mining Architecture
... To aid program testing efforts and help program verification tools to find bugs and ensure correctness of systems the mined specifications can be used. Mining of specification process starts with a program under analysis ...
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Semantic Suffix Net Clustering for Search Results
... a semantic suffix tree as a structure to represent snippets and then tree pruning to combine related ...to semantic search results clustering by using the semantic suffix net as a structure to ...
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The Impact of Presenting Semantically Related Clusters of New Words on Iranian Intermediate EFL learners' Vocabulary Acquisition
... Is it easy for learner to remember a group of new words if they are too similar? So far, two theories introduced about the similarity of words that will be discussed below. The interference theory "hypothesizes that ...
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Building a Lightweight Semantic Model for Unsupervised Information Extraction on Short Listings
... listing-focused clustering mod- ule that helps group together extracted tokens of same ...the semantic model learned by these two modules is effective across multiple ...
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Semantic Word Clusters Using Signed Spectral Clustering
... cannot-link clustering. Furthermore, they note that cannot-link clustering does not improve per- formance whereas our signed clustering antonyms are ...
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Dual sticky hierarchical Dirichlet process hidden Markov model and its application to natural language description of motions
... One of the most challenging problems in computer vision is to understand and semantically interpret object motions in dynamic image sequences. For instance, a visual surveillance system should be able to interpret what ...
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Semantic Based Document Clustering Using Lexical Chains
... the semantic relationships among documents so that cannot accurately represent cluster of the ...introducing semantic information from ontology such as WordNet has been widely used to improve the quality of ...
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Using a Wikipedia based Semantic Relatedness Measure for Document Clustering
... Computing semantic relatedness between two texts requires: (1) to estimate relatedness between two sets of nodes in the network, as described in Sections 3 and 4; and (2) to project each text onto a set of nodes, ...
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Semantic Based Multilingual Document Clustering via Tensor Modeling
... To the best of our knowledge, existing clustering ap- proaches for comparable corpora are customized for a small set (two or three) of languages (Montalvo et al., 2007). Most of them are not generalizable to many ...
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