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This work addresses information needs that have a temporal dimension conveyed by a temporal expression in the user’s query. Temporal expressions such as “in the 1990s” are frequent, easily extractable, but not leveraged by existing retrieval models. One challenge when dealing with them is their inherent uncertainty. It is often unclear which exact time(More)
Relevance evaluation is an essential part of the development and maintenance of information retrieval systems. Yet traditional evaluation approaches have several limitations; in particular, conducting new editorial evaluations of a search system can be very expensive. We describe a new approach to evaluation called TERC, based on the crowdsourcing paradigm,(More)
In the last years crowdsourcing has emerged as a viable platform for conducting relevance assessments. The main reason behind this trend is that makes possible to conduct experiments extremely fast, with good results and at low cost. However, like in any experiment, there are several details that would make an experiment work or fail. To gather useful(More)
Recently, Amazon Mechanical Turk has gained a lot of attention as a tool for conducting different kinds of relevance evaluations. In this paper we show a series of experiments on TREC data, evaluate the outcome, and discuss the results. Our position, supported by these preliminary experimental results, is that crowdsourcing is a viable alternative for(More)
Time is an important dimension of any information space and can be very useful in information retrieval. Current information retrieval systems and applications do not take advantage of all the time information available in the content of documents to provide better search results and user experience. In this paper we show some of the areas that can benefit(More)
Time is an important dimension of any information space and can be very useful in information retrieval and in particular clustering and exploration of search results. Search result clustering is a feature integrated in some of today's search engines, allowing users to further explore search results. However, only little work has been done on exploiting(More)
Time is an important dimension of any information space. It can be very useful for a wide range of information retrieval tasks such as document exploration, similarity search, summarization, and clustering. Traditionally, information retrieval applications do not take full advantage of all the temporal information embedded in documents to provide(More)
Very recently crowdsourcing has become the de facto platform for distributing and collecting human computation for a wide range of tasks and applications such as information retrieval, natural language processing and machine learning. Current crowdsourcing platforms have some limitations in the area of quality control. Most of the effort to ensure good(More)
Crowdsourcing has emerged as a viable platform for conducting different types of relevance evaluation. The main reason behind this trend is that it makes possible to conduct experiments extremely fast, with good results at a low cost. However, like in any experiment, there are several implementation details that would make an experiment work or fail. To(More)