Search (3 results, page 1 of 1)

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Abstract

Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata. This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative search. We propose a ranking model for each task that integrates the individual user's tagging history in the recommendation of tags and content, to align its suggestions to the individual user preferences. We demonstrate on two real data sets that for all three tasks, the personalized ranking should take into account both the user's own preference and the opinion of others.

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Abstract

A database management system is a general-purpose software system that facilitates the processes of defining, constructing, and manipulating databases for various applications. This article investigates the role of data management in multimedia digital libraries, and its implications for the design of database management systems. The notions of content abstraction and content independence are introduced, which clearly expose the unique challenges (for database architecture) of applications involving multimedia search. A blueprint of a new class of database technology is proposed, which supports the basic functionality for the management of both content and structure of multimedia objects

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Abstract

Existing methods for automatically analyzing search logs describe search behavior on the basis of syntactic differences (overlapping terms) between queries. Although these analyses provide valuable insights into the complexity and successfulness of search interactions, they offer a limited interpretation of the observed searching behavior, as they do not consider the semantics of users' queries. In this article we propose a method to exploit semantic information in the form of linked data to enrich search queries so as to determine the semantic types of the queries and the relations between queries that are consecutively entered in a search session. This work provides also an in-depth analysis of the search logs of professional users searching a commercial picture portal. Compared to previous image search log analyses, in particular those of professional users, we consider a much larger dataset. We analyze the logs both in a syntactic way and using the proposed semantic approach and compare the results. Our findings show the benefits of using semantics for search log analysis: the identified types of query modifications cannot be appropriately analyzed by only considering term overlap, since queries related in the most frequent ways do not usually share terms.