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Showing papers by "Sarvnaz Karimi published in 2012"


Proceedings ArticleDOI
29 Oct 2012
TL;DR: This work demonstrates the ESA (Emergency Situation Awareness) system that mines microblogs in real-time to extract and visualise useful information about incidents and their impact on the community in order to equip the right authorities and the general public with situational awareness.
Abstract: During a disastrous event, such as an earthquake or river flooding, information on what happened, who was affected and how, where help is needed, and how to aid people who were affected, is crucial. While communication is important in such times of crisis, damage to infrastructure such as telephone lines makes it difficult for authorities and victims to communicate. Microblogging has played a critical role as an important communication platform during crises when other media has failed. We demonstrate our ESA (Emergency Situation Awareness) system that mines microblogs in real-time to extract and visualise useful information about incidents and their impact on the community in order to equip the right authorities and the general public with situational awareness.

56 citations


Journal ArticleDOI
TL;DR: This paper quantifies the potential benefits of tagging users' targeted concepts in queries and documents in domain-specific information retrieval using biomedical research documents and finds no evidence that automatic concept recognition in general is of significant value for this task.
Abstract: In ad hoc querying of document collections, current approaches to ranking primarily rely on identifying the documents that contain the query terms. Methods such as query expansion, based on thesaural information or automatic feedback, are used to add further terms, and can yield significant though usually small gains in effectiveness. Another approach to adding terms, which we investigate in this paper, is to use natural language technology to annotate - and thus disambiguate - key terms by the concept they represent. Using biomedical research documents, we quantify the potential benefits of tagging users' targeted concepts in queries and documents in domain-specific information retrieval. Our experiments, based on the TREC Genomics track data, both on passage and full-text retrieval, found no evidence that automatic concept recognition in general is of significant value for this task. Moreover, the issues raised by these results suggest that it is difficult for such disambiguation to be effective.

13 citations


Proceedings Article
01 Nov 2012
TL;DR: The most important finding is highlighting the value of systematic pre-processing of tweets and its impact on improving the effectiveness of search.
Abstract: : We report on the participation of the CSIRO team in the TREC 2012 Microblog Track. We participated with four automatic runs for the ad hoc search task and four automatic runs for the filtering task. In the ad hoc search task, we experiment with different pre-processing and query expansion techniques. Our most important finding is highlighting the value of systematic pre-processing of tweets and its impact on improving the effectiveness of search. In the filtering task, we apply different feature extraction and classification techniques. We demonstrate the potential of using SVM classifiers for filtering tweets for a given topic.

12 citations