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Erschienen in:
BFST_ED: A Novel Upper Bound Computation Framework for the Graph Edit Distance Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Context Semantic Analysis: A Knowledge-Based Technique for Computing Inter-document Similarity

verfasst von : Fabio Benedetti, Domenico Beneventano, Sonia Bergamaschi

Erschienen in: Similarity Search and Applications

Verlag: Springer International Publishing

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Abstract

We propose a novel knowledge-based technique for inter-document similarity, called Context Semantic Analysis (CSA). Several specialized approaches built on top of specific knowledge base (e.g. Wikipedia) exist in literature but CSA differs from them because it is designed to be portable to any RDF knowledge base. Our technique relies on a generic RDF knowledge base (e.g. DBpedia and Wikidata) to extract from it a vector able to represent the context of a document. We show how such a Semantic Context Vector can be effectively exploited to compute inter-document similarity. Experimental results show that our general technique outperforms baselines built on top of traditional methods, and achieves a performance similar to the ones of specialized methods.

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Vorheriges Kapitel Domain Graph for Sentence Similarity
Nächstes Kapitel An Experimental Survey of MapReduce-Based Similarity Joins
Fußnoten
2
We abbreviate URI namespaces with common prefixes, see http://​prefix.​cc for details.
 
4
When an entity is an instance of more than one class we use the class with the minor number of instances because it better characterizes an entity; however if we filter the knowledge bases by excluding classes defined in external sources such as YAGO, GroNames, etc. only 6.4 % of entities in Dbpedia and 2.22 % in Wikidata are instances of more than one class.
 
6
Implemented as in [15] (only removing the stopwords).
 
7
If not explicitly stated all the difference in performance are statistically significant at \(p{\text {-}}value < 0.05\) using Fisher’s Z-value transformation.
 
8
The sets of starting entities are obtained by using NER APIs.
 
9
With td-idf as weighting function.
 
11
We executed this experiment in a Ubuntu machine with 16 cores (Intel Xeon E312xx) and 98 Gb of RAM.
 
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Metadaten
Titel
Context Semantic Analysis: A Knowledge-Based Technique for Computing Inter-document Similarity
verfasst von
Fabio Benedetti
Domenico Beneventano
Sonia Bergamaschi
Copyright-Jahr
2016
Buch
Similarity Search and Applications

Print ISBN: 978-3-319-46758-0

Electronic ISBN: 978-3-319-46759-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-46759-7_13

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