Sergio Navarro

Multiple approaches to analysing query diversity

In this paper we examine user queries with respect to diversity: providing a mix of results across different interpretations. Using two query log analysis techniques (click entropy and reformulated queries), 14.9 million queries from the Microsoft Live Search log were analysed. We found that a broad range of query types may benefit from diversification. Additionally, although there is a correlation between word ambiguity and the need for diversity, the range of results users may wish to see for an ambiguous query stretches well beyond traditional notions of word sense.

IR-n in the CLEF robust WSD task 2008

In our approach to the Robust WSD task we have used a passage based system jointly with a WordNet and WSD based term expansion for the documents and queries. Furthermore, we have experimented with two well known relevance feedback methods - LCA and PRF -, in order to figure out which is more suitable to take profit of the WSD query expansion based on Wordnet. Our best run has obtained a 4th - 0.4008 MAP -. A major finding is that LCA fits better than PRF to this task due to it is able to take advantage of the expanded documents and queries.

Using evidences based on natural language to drive the process of fusing multimodal sources

This paper focuses on the proposal and evaluation of two multimodal fusion techniques in the field of Visual Information Retrieval (VIR). These proposals are based on two widely used fusion strategies in the VIR area, the multimodal blind relevance feedback and the multimodal re-ranking strategy. Unlike the existent techniques, our alternative proposals are guided by the evidence found in the natural language annotations related to the images. The results achieved by our runs in two different ImageCLEF tasks, 3rd place in the Wikipedia task [1] and 4th place within all the automatic runs in the photo task [2], jointly with the results obtained in later experiments presented in this paper show us that the use of conceptual information associated with an image can improve significantly the performance of the original multimodal fusion techniques used.

Combining TEXT-MESS systems at ImageCLEF 2008

This paper describes the joint work of two teams belonging to the TEXT-MESS project. The system presented at ImageCLEFPhoto task combines one module based on filtering and other based on clustering. The main objective was to study the behavior of these methods with a large number of configurations in order to increase our chances of success. The system presented at ImageCLEFmed task uses the IR-n system with a negative query expansion based on the acquisition type of the image mixed with the SINAI system with a MeSH based query expansion.

Analysing an Approach to Information Retrieval of Visual Descriptions with IR-n, a System Based on Passages

This paper analyses an approach made to the development of a textual image retrieval system by the University of Alicante using IR-n, a text-based information retrieval (IR) system. With only a minimal amount of adaptations to the features of this task, our system has obtained precision results above the mean average of participants for ImageCLEF07 both for English (0.1604 vs 0.1388) and for Spanish (0.1482 vs 0.1450). For German, our results were below the mean (0.0991 vs 0.1331), which could be due to the fact that our system does not incorporate a splitter for the treatment of this agglutinative language. These results are obtained without the incorporation of image recovery dominion techniques. The error analysis shows us that there is still a considerable amount of work to do concerning text-based techniques in order to improve the system, but also shows that the key to successful participation in this task is to mix text and image resources.

Diversity promotion: is reordering top-ranked documents sufficient?

In our participation in the ImageCLEF 2009 Photo Retrieval task we pursued two objectives: Firstly, to re-evaluate MultiModal Local Context Analysis (MMLCA), our multimodal fusion technique. Secondly, to evaluate a new subquery generation technique based on clustering. From the experiments conducted: Firstly, we confirmed MMLCA performs better for generic domain collections than the other local expansion techniques evaluated. Secondly, our proposal of subquery generation based on clustering, obtained good results (5th best textual run of the Photo Retrieval task). Besides these results in this paper we try to reflect on the extent to which reordering techniques are appropriate to promote diversity. Results suggest that while reordering strategies limit the margin of improvement due to their use of a limited number of documents, the use of approaches based on subqueries generation can overcome this limitation.