Measuring Similarity for Short Texts on Social Media

In this paper, we present a method for measuring semantic similarity between short texts by combining two different kinds of features: (1) distributed representation of word, (2) knowledge-based and corpus-based metrics. Then, we present experiments to evaluate our method on two popular datasets - M...

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Bibliographic Details
Published inComputational Social Networks Vol. 9795; pp. 249 - 259
Main Authors Duong, Phuc H., Nguyen, Hien T., Huynh, Ngoc-Tu
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2016
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Convolutional Neural Network
Information retrieval
Latent Dirichlet Allocation
Latent Semantic Analysis
Query Expansion
Semantic Similarity
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Summary:In this paper, we present a method for measuring semantic similarity between short texts by combining two different kinds of features: (1) distributed representation of word, (2) knowledge-based and corpus-based metrics. Then, we present experiments to evaluate our method on two popular datasets - Microsoft Research Paraphrase Corpus and SemEval-2015. The experimental results show that our method achieves state-of-the-art performance.
ISBN:9783319423449
3319423444
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-42345-6_22