scholarly journals Collaboration, Reputation and Recommender Systems in Social Web Search

2015 ◽  
pp. 569-608 ◽  
Author(s):  
Barry Smyth ◽  
Maurice Coyle ◽  
Peter Briggs ◽  
Kevin McNally ◽  
Michael P. O’Mahony
Keyword(s):  
Recommender Systems ◽  
Web Search ◽  
Social Web

Social Web Search

2014 ◽  
pp. 1930-1935 ◽  
Author(s):  
Maryam Shoaran ◽  
Alex Thomo ◽  
Jens Weber
Keyword(s):  
Web Search ◽  
Social Web

Workshop on recommender systems and the social web

2009 ◽  
Author(s):  
Dietmar Jannach ◽  
Werner Geyer ◽  
Casey Dugan ◽  
Jill Freyne ◽  
Sarabjot Singh Anand ◽  
...  
Keyword(s):  
Recommender Systems ◽  
Social Web ◽  
The Social

scholarly journals Recommendation as Collaboration in Web Search

AI Magazine ◽  
2011 ◽  
Vol 32 (3) ◽  
pp. 35-45 ◽  
Author(s):  
Barry Smyth ◽  
Jill Freyne ◽  
Maurice Coyle ◽  
Peter Briggs
Keyword(s):  
Recommender Systems ◽  
Search Engines ◽  
Web Search ◽  
Online Information ◽  
Information Discovery ◽  
Proactive Approach ◽  
Systems Research ◽  
Traditional Approaches ◽  
New Generation

Recommender systems now play an important role in online information discovery, complementing traditional approaches such as search and navigation, with a more proactive approach to discovery that is informed by the users interests and preferences. To date recommender systems have been deployed within a variety of e-commerce domains, covering a range of products such as books, music, movies, and have proven to be a successful way to convert browsers into buyers. Recommendation technologies have a potentially much greater role to play in information discovery however and in this article we consider recent research that takes a fresh look at web search as a fertile platform for recommender systems research as users demand a new generation of search engines that are less susceptible to manipulation and more responsive to searcher needs and preferences.

A web search-centric approach to recommender systems with URLs as minimal user contexts

2011 ◽  
Vol 84 (6) ◽  
pp. 930-941 ◽  
Author(s):  
W.K. Chan ◽  
Yuen Yau Chiu ◽  
Yuen Tak Yu
Keyword(s):  
Recommender Systems ◽  
Web Search

3rd workshop on recommender systems and the social web

2011 ◽  
Author(s):  
Jill Freyne ◽  
Sarabjot Singh Anand ◽  
Ido Guy ◽  
Andreas Hotho
Keyword(s):  
Recommender Systems ◽  
Social Web ◽  
The Social

Clustering of the Web Search Results in Educational Recommender Systems

2012 ◽  
pp. 154-181 ◽  
Author(s):  
Constanta-Nicoleta Bodea ◽  
Maria-Iuliana Dascalu ◽  
Adina Lipai
Keyword(s):  
Recommender Systems ◽  
Clustering Algorithm ◽  
Web Search ◽  
Web Pages ◽  
Lexical Database ◽  
Assessment Task ◽  
Search Results ◽  
Meta Search ◽  
Search Approach ◽  
The Web

This chapter presents a meta-search approach, meant to deliver bibliography from the internet, according to trainees’ results obtained at an e-assessment task. The bibliography consists of web pages related to the knowledge gaps of the trainees. The meta-search engine is part of an education recommender system, attached to an e-assessment application for project management knowledge. Meta-search means that, for a specific query (or mistake made by the trainee), several search mechanisms for suitable bibliography (further reading) could be applied. The lists of results delivered by the standard search mechanisms are used to build thematically homogenous groups using an ontology-based clustering algorithm. The clustering process uses an educational ontology and WordNet lexical database to create its categories. The research is presented in the context of recommender systems and their various applications to the education domain.

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