M-Dyaa Albakour

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This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing,(More)
Search applications have become very popular over the last two decades, one of the main drivers being the advent of the Web. Nevertheless, searching on the Web is very different to searching on smaller, often more structured collections such as digital libraries, local Web sites, and intranets. One way of helping the searcher locating the right information(More)
Local search is increasingly attracting more demand, whereby the users are interested to find out about places or events in their local vicinity. In this paper, we propose to use the Twitter microblogging platform to detect and rank local events of interest in real-time. We present a novel event retrieval framework, where both the contents of the tweets and(More)
User evaluations of search engines are expensive and not easy to replicate. The problem is even more pronounced when assessing adap-tive search systems, for example system-generated query modification suggestions that can be derived from past user interactions with a search engine. Automatically predicting the performance of different modification(More)
In this paper, we approach the problem of real-time filtering in the Twitter Microblogging platform. We adapt an effective traditional news filtering technique, which uses a text classifier inspired by Rocchio's relevance feedback algorithm, to build and dynamically update a profile of the user's interests in real-time. In our adaptation, we tackle two(More)
Modern search engines have been moving away from very simplistic interfaces that aimed at satisfying a user's need with a single-shot query. Interactive features such as query suggestions and faceted search are now integral parts of Web search engines. Generating good query modification suggestions or alternative queries to assist a searcher remains however(More)
In TREC 2012, we focus on tackling the new challenges posed by the Medical, Microblog and Web tracks, using our Terrier Information Retrieval Platform. In particular, for the Medical track, we investigate how to exploit implicit knowledge within medical records, with the aim of better identifying those records from patients with specific medical conditions.(More)
In TREC 2014, we focus on tackling the challenges posed by the Contextual Suggestion and Temporal Summarisa-tion tracks, as well as enhancing our existing technologies to tackle risk-sensitivity as part of the Web track, building upon our Terrier Information Retrieval Platform. In particular , for the Contextual Suggestion track, we propose a novel bundled(More)