Jesus A. Rodriguez Perez

Predicting query performance in microblog retrieval

Query Performance Prediction (QPP) is the estimation of the retrieval success for a query, without explicit knowledge about relevant documents. QPP is especially interesting in the context of Automatic Query Expansion (AQE) based on Pseudo Relevance Feedback (PRF). PRF-based AQE is known to produce unreliable results when the initial set of retrieved documents is poor. Theoretically, a good predictor would allow to selectively apply PRF-based AQE when performance of the initial result set is good enough, thus enhancing the overall robustness of the system. QPP would be of great benefit in the context of microblog retrieval, as AQE was the most widely deployed technique for enhancing retrieval performance at TREC. In this work we study the performance of the state of the art predictors under microblog retrieval conditions as well as introducing our own predictors. Our results show how our proposed predictors outperform the baselines significantly.

On using inter-document relations in microblog retrieval

Microblog Ad-hoc retrieval has received much attention in recent years. As a result of the high vocabulary diversity of the publishing users, a mismatch is formed between the queries being formulated and the tweets representing the actual topics. In this work, we present a re-ranking approach relying on inter-document relations, which attempts to bridge this gap. Experiments with TRECs Microblog 2012 collection show that including such information in the retrieval process, statistically significantly improves retrieval effectiveness in terms of Precision and MAP, when the baseline performs well as a starting point.

CoFox: a visual collaborative browser

This paper outlines the preliminary design of a novel synchronous collaborative web browsing system named CoFox. CoFox differs from other collaborative web browsing systems in that it provides a live video stream of web content being viewed by the remote user as the main awareness supporting mechanism. Additionally, it allows users to scroll through the remote user video screen capture to re-watch any part of the search session. As well as screen capture features, also included is a set of collaboration tools including video segment annotations, shared links and instant messaging. CoFox provides a platform for a pair of users to tackle collaborative tasks; which may greatly benefit from the expertise of more than one individual. We outline the graphical user interface components from which CoFox will be composed, the hypothetical benefits provided by such a system and finally describe a possible user-based evaluation methodology.

On Microblog Dimensionality and Informativeness: Exploiting Microblogs' Structure and Dimensions for Ad-Hoc Retrieval

In recent years, microblog services such as Twitter have gained increasing popularity, leading to active research on how to effectively exploit its content. Microblog documents such as tweets differ in morphology with respect to more traditional documents such as web pages. Particularly, tweets are considerably shorter (140 characters) than web documents and contain contextual tags regarding the topic (hashtags), intended audience (mentions) of the document as well as links to external content(URLs). Traditional and state of the art retrieval models perform rather poorly in capturing the relevance of tweets, since they have been designed under very different conditions. In this work, we define a microblog document as a high-dimensional entity and study the structural differences between those documents deemed relevant and those non-relevant. Secondly we experiment with enhancing the behaviour of the best observed performing retrieval model by means of a re-ranking approach that accounts for the relative differences in these dimensions amongst tweets. Additionally we study the interactions between the different dimensions in terms of their order within the documents by modelling relevant and non-relevant tweets as state machines. These state machines are then utilised to produce scores which in turn are used for re-ranking. Our evaluation results show statistically significant improvements over the baseline in terms of precision at different cut-off points for both approaches. These results confirm that the relative presence of the different dimensions within a document and their ordering are connected with the relevance of microblogs.