On the issue of aggregation in Information Retrieval

Abstract:

This lecture will address the issue of defining flexible approaches to Information Retrieval by means of the usage of aggregation operators in various phases of the retrieval process. In particular, these approaches rely on the interpretation of Information Retrieval as a Multi-Criteria Decision Making (MCDM) problem, from various perspectives. The first, more straightforward perspective,  is to interpret the overall IR process as a MCDM process aimed at selecting the best alternatives (documents) based on the assessment of the performance of multiple criteria (the keywords specified in a user’s query). Another and strongly related perspective is to see the assessment of the overall relevance estimate of a document (still an alternative) to a query as the process of evaluating the performance of several relevance dimensions (e.g., topicality, novelty, recency, etc.), which in this case represent the criteria to be aggregated. Another process that may require the application of appropriate aggregation operators is the indexing process, when applied to structured documents.

Metasearch constitutes another interesting task that can be seen as an instance of a Multi-Expert Decision Making (MEDM) problem, also strongly relying on the appropriate choice of an aggregation operator. By this task a user query is separately evaluated by different search engines, each one providing its own relevance assessment of the considered documents. Metasearch aims to merge the ranked lists generated by the various search engines (experts) in response to a query, to the aim of providing a unique, consensual ranked list of results.

Despite the potential impact of aggregation on the whole IR process, this aspect has not received the proper attention in the literature. Only recently some approaches have appeared demonstrating the importance of this issue, and its potential impact on the searching process. This seminar aims to shortly review the main contributions that in the literature have made use of aggregation operators in Information Retrieval.

Biography:

Gabriella Pasi is Full Professor at the Department of Informatics, Systems and Communication, at the University of Milano Bicocca, Milano, Italy; within DISCo she leads the Information Retrieval Lab. Her main research activities are related to Information Retrieval and Information Filtering. In recent years she has addressed the issues of contextual search and user modelling. She is also conducting research activities related to the analysis of user generated content on social media. She has published more than 200 papers on International Journals and Books, and on the Proceedings of International Conferences. She is involved in several activities for the evaluation of research; in particular, she was appointed as an expert of the Computer Science panel for the Starting Grants (till 2011), and Consolidator Grants (2012) of the Programme Ideas at the European Research Council. Since 2013 she is the President of the European Society for Fuzzy Logic an d Technologies (EUSFLAT). She is a member of the Editorial Board of several international journals, and she has delivered several keynote talks/plenary lectures at international conferences related to her research interests. She has participated to the organization of several International events, in both roles of organization and program chair.