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Towards a Better Contextualization of Web Contents via Entity-Level Analytics

Authors
  • Kumar, Amit1
  • 1 Université de Caen Normandie,
Type
Published Article
Journal
Advances in Information Retrieval
Publication Date
Mar 24, 2020
Volume
12036
Pages
613–618
Identifiers
DOI: 10.1007/978-3-030-45442-5_80
PMCID: PMC7148069
Source
PubMed Central
Keywords
Disciplines
  • Article
License
Unknown

Abstract

With the abundance of data and wide access to the internet, a user can be overwhelmed with information. For an average Web user, it is very difficult to identify which information is relevant or irrelevant. Hence, in the era of continuously enhancing Web, organization and interpretation of Web contents are very important in order to easily access the relevant information. Many recent advancements in the area of Web content management such as classification of Web contents, information diffusion, credibility of information, etc. have been explored based on text and semantic of the document. In this paper, we propose a purely semantic contextualization of Web contents. We hypothesize that named entities and their types present in a Web document convey substantial semantic information. By extraction of this information, we aim to study the reasoning and explanation behind the Web contents or patterns. Furthermore, we also plan to exploit LOD (Linked Open Data) to get a deeper insight of Web contents.

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