DOCTORAL ABSTRACT

Diversity-oriented Multimodal and Interactive Information Retrieval
Rodrigo Tripodi Calumby
RECOD Lab, University of Campinas, Brazil
University of Feira de Santana, Brazil.
rtcalumby@uefs.br
Abstract

Information retrieval methods, especially considering multimedia data, have evolved towards theintegration of multiple sources of evidence in the analysis of the relevance of the items considering agiven user search task. In this context, for attenuating the semantic gap between low-level features
extracted from the content of the digital objects and high-level semantic concepts (objects, categories,etc.) and making the systems adaptive to different user needs, interactive models have brought theuser closer to the retrieval loop allowing user-system interaction mainly through implicit or explicit
relevance feedback. Analogously, diversity promotion has emerged as an alternative for tacklingambiguous or underspecified queries. Additionally, several works have addressed the issue ofminimizing the required user effort on providing relevance assessments while keeping an acceptable
overall effectiveness.
This thesis discusses, proposes, and experimentally analyzes multimodal and interactive
diversity-oriented information retrieval methods. This work, comprehensively covers the interactive
information retrieval literature and also discusses about recent advances, the great researchchallenges, and promising research opportunities. We have proposed and evaluated two relevancediversity trade-off enhancement work-flows, which integrate multiple information from images, suchas: visual features, textual metadata, geographic information, and user credibility descriptors. In turn,as an integration of interactive retrieval and diversity promotion techniques, for maximizing thecoverage of multiple query interpretations/aspects and speeding up the information transfer between
the user and the system, we have proposed and evaluated a multimodal online learning-to-rank
method trained with relevance feedback over diversified results.
Our experimental analysis shows that the joint usage of multiple information sources
positively impacted the relevance-diversity balancing algorithms. Our results also suggest that theintegration of multimodal-relevance-based filtering and reranking is effective on improving result
relevance and also boosts diversity promotion methods. Beyond it, with a thorough experimental
analysis we have investigated several research questions related to the possibility of improving result
diversity and keeping or even improving relevance in interactive search sessions. Moreover, weanalyze how much the diversification effort affects overall search session results and how different
diversification approaches behave for the different data modalities. By analyzing the overall and per
feedback iteration effectiveness, we show that introducing diversity may harm initial results whereas
it significantly enhances the overall session effectiveness not only considering the relevance anddiversity, but also how early the user is exposed to the same amount of relevant items and diversity.
Supervisor: Ricardo da Silva Torres, University of Campinas, Brazil, rtorres@ic.unicamp.br
Available at: http://www.bibliotecadigital.unicamp.br/document/?code=000963167&lg=en_US

ACM SIGIR Forum86

Vol. 50 No. 1 June 2016