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Subject: search.filters.subject.Information Retrieval

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    Item type:Publication,
    CoZpace: A proposal for collaborative web search for sharing search records and interactions
    (2014-10-14)
    Kruajirayu, Hannarin
    ;
    Tangsomboon, Ake
    ;
    Leelanupab, Teerapong
    Today's search systems are mainly designed for one user to use individually. Search activities in practice can, however, be conducted by two or more users working together. This is due to the fact that information seeking tasks are complex and often requires multiple users' efforts to collaboratively assess and search for relevant information. In some tasks, there is a large amount of information to search or such information requires human intelligence to judge whether it is relevant to information needs. This paper introduces the development of collaborative search system, named "CoZpace". CoZpace is a Web-based application, which allows a pair or a group of users to create a collaborative search task. Within the created task, a user can invite and communicate with other members in a group, share search history records, and mark search results considered relevant. We also propose a newly developed feature, called "snapboard", to support collaborative search activities. With the snapboard, users are allowed to take a snapshot of a part of focused information in a Web site and then share it among collaborators on a display board. A user can mark it as relevant or comment it for further reviews of other collaborators.
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    Item type:Publication,
    Indexing without spam
    (2011-12-01)
    Zuccon, Guido
    ;
    Leelanupab, Teerapong
    ;
    Nguyen, Anthony
    ;
    Azzopardi, Leif
    The presence of spam in a document ranking is a major issue for Web search engines. Common approaches that cope with spam remove from the document rankings those pages that are likely to contain spam. These approaches are implemented as post-retrieval processes, that filter out spam pages only after documents have been retrieved with respect to a user's query. In this paper we propose removing spam pages at indexing time, therefore obtaining a pruned index that is virtually "spam-free". We investigate the benefits of this approach from three points of view: indexing time, index size, and retrieval performance. Not surprisingly, we found that the strategy decreases both the time required by the indexing process and the space required for storing the index. Surprisingly instead, we found that by considering a spam-pruned version of a collection's index, no difference in retrieval performance is found when compared to that obtained by traditional post-retrieval spam filtering approaches.