An Approach to Social News Recommendation based on Focused Crawling and Sentiment Analysis
Pages 111 - 112
Abstract
News recommendation poses several specific challenges compared to other domains, such as freshness and serendipity. The proposed research will develop new methods and techniques to address some of such challenges. With the aim of handling the users' changing interests and the fast evolution overtime of news, my solution will be proposed in the social network domain, exploiting an adaptive focused crawling algorithm. Moreover, it will consider a given user's attitude towards her interests, with the purpose of recommending articles in line with her beliefs. An experimental evaluation is currently being implemented to assess the effectiveness of my approach, also in comparison with state-of-the-art techniques.
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Index Terms
- An Approach to Social News Recommendation based on Focused Crawling and Sentiment Analysis
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Published In
July 2017
456 pages
ISBN:9781450350679
DOI:10.1145/3099023
- Editors:
- Marko Tkalcic,
- Dhaval Thakker,
- Panagiotis Germanakos,
- Kalina Yacef,
- Cecile Paris,
- Olga Santos,
- General Chairs:
- Maria Bielikova,
- Eelco Herder,
- Program Chairs:
- Michel Desmarais,
- Federica Cena
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Association for Computing Machinery
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Published: 09 July 2017
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UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization
July 9 - 12, 2017
Bratislava, Slovakia
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