University of Lugano at TREC 2015: Contextual Suggestion and Temporal Summarization Tracks
Mohammad Aliannejadi, Seyed Ali Bahrainian, Anastasia Giachanou, Fábio Crestani · Text REtrieval Conference · 2015
This technical report presents the work of the University of Lugano at TREC 2015 Contextual Suggestion and Temporal Summarization tracks. The first track that we report on, is the Contextual Suggestion. The goal of the Contextual Suggestion track is to develop systems that could generate user-specific suggestions that a user might potentially like. Our proposed method attempts to model the users’ behavior and interest using a classifier, and enrich the basic model using additional data sources. Our results illustrate that our proposed method performed very well in terms of all used evaluation metrics. The second track that we report on, is the Temporal Summarization that aims to develop systems that can detect useful, new, and timely updates about a certain event. Our proposed method selects sentences that are relevant and novel to a specific event with the aim to create a summary for this event. The results showed that the proposed method is very e↵ective in terms of Latency Comprehensiveness (LC). However, the approach did not manage to obtain a good performance in terms of Expected Latency Gain (ELG).