[PDF] Top 20 Evaluating text coherence based on semantic similarity graph
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Evaluating text coherence based on semantic similarity graph
... The text is said to be less coherent if it exhibits many atten- tion shifts, ...a text mentioning the same ...representing text as a matrix called Entity Grid in which the col- umn corresponds to ... See full document
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Detection of medical text semantic similarity based on convolutional neural network
... use graph struc- tures [19] to represent the relationships among medical ...methods. Graph embedding technology embeds edge and node information of graphs into low dimensional dense vectors [20], and we ... See full document
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Graph Based Similarity Measures for Synonym Extraction from Parsed Text
... 2006). Graph-based methods have been successfully ap- plied to evaluate word similarity using available on- tologies, where the underlying graph included word senses and semantic ... See full document
5
A Graph-based Text Similarity Measure That Employs Named Entity Information
... For evaluating the performance of the proposed text similarity measure in a text clustering task, we used a simple, centroid-based, clustering al- gorithm ...a text ... See full document
7
Friendbook: Semantic Based Friendship
... recommendation based on social graph may not be most relevant to reflect user’s expectation on friend ...approach Based on novel semantic friend recommendation includes life-styles ... See full document
5
Evaluating Semantic Resemblance of Perception in Data Graphs
... ABSTRACT--This script presents a purpose for scaling the semantic similarity between concepts in Knowledge Graphs (KGs) corresponding to WordNet and DBpedia. Previous entice linguistic resemblance purposes ... See full document
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Text to Text Semantic Similarity for Automatic Short Answer Grading
... C-Rater (Leacock and Chodorow, 2003) matches the syntactical features of a student response (subject, object, and verb) to that of a set of correct responses. The method specifically disregards the bag-of-words approach ... See full document
9
Investigating Semantic Properties of Images Generated from Natural Language Using Neural Networks
... the text as individual words, bi-grams, tri-grams, or n-grams, and bagging the ...vectorized based on the probabilities of its surrounding words, in an attempt to encapsulate and capture the context of ... See full document
74
Text Graph An Enhanced Graph Fusion Model for Document Clustering
... OPTICS), graph theory (CLICK, MST). In document clustering, the text is characterized by statistical and semantics models ...The semantic portrayal is a semantically arranged ...the semantic ... See full document
5
Evaluating Topic Coherence Using Distributional Semantics
... cosine similarity using PMI is consistently higher ...cosine similarity scores in the reduced semantic space are higher than average PMI and NPMI in all of the datasets, demonstrating that ... See full document
9
Improved semantic graph-based plagiarism detection
... Text Graph-Based Representation does not only represent the content of a text document as a graph, but it also captures the underlying semantic meaning in terms of the ... See full document
45
Automatic and Human Scoring of Word Definition Responses
... tic similarity that uses Markov chains on a graph of term relations to perform a kind of semantic smooth- ...compute text seman- tic ...cosine similarity baseline in ranking quality and ... See full document
8
Using a Graph based Coherence Model in Document Level Machine Translation
... entity graph to the lexical graph: two sentences may be semantically connected because at least two words of them are semantically associated to each ...compute semantic relatedness be- tween all ... See full document
10
Using Semantic Distance to Automatically Suggest Transfer Course Equivalencies
... Table 1. Number of courses in the data sets Consider the small data set as an illustration. Each of the 25 MCC courses is compared with all 24 UML courses. All words are converted to low- ercase and punctuation is ... See full document
10
Similarity Driven Semantic Role Induction via Graph Partitioning
... multi-layer graph partitioning ...cluster similarity in the two ways described above: (a) by finding for each instance in one cluster the instance in the other cluster that is maximally similar or ... See full document
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A Survey of Text Similarity Approaches
... a semantic space from word ...the text is analyzed, a focus word is placed at the beginning of a ten word window that records which neighboring words are counted as ...differently based on whether ... See full document
6
Big Data Analytics Tools, Methods & Frameworks: A Comprehensive Review
... Big data refer to the collection of new information which must be made handy to high numbers of users close to real time, based on gigantic data inventories from multiple sources, with the goal of speeding up ... See full document
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Evaluating the effect of annotation size on measures of semantic similarity
... We perform all our experiments using the Gene Ontology (GO) [13], downloaded on 22 December 2015 from http:// geneontology.org/page/download-ontology and Human Phenotype Ontology (HPO) [14], download on 1 April 2016 from ... See full document
10
Graph based Local Coherence Modeling
... bipartite graph are defined following the linguistic intuition that subjects are more important than ob- jects, which are themselves more important than other syntactic ...local coherence value than less ... See full document
11
Better Together: Combining Language and Social Interactions into a Shared Representation
... Distance-based Features Given a node pair rep- resented by their k-dimensional node embedding, we generate features for the pair according to nine similarity measures. The nine measures used by us are ... See full document
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