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Journals and Conferences
Prior-art search is a critical step in the examination procedure of a patent application. This study explores automatic query generation from patent documents to facilitate the time-consuming and labor-intensive search for relevant patents. It is essential for this task to identify discriminative terms in different sections of a query patent, which enable… (More)
This paper addresses blog feed retrieval where the goal is to retrieve the most relevant blog feeds for a given user query. Since the retrieval unit is a blog, as a collection of posts, performing relevance feedback techniques and selecting the most appropriate documents for query expansion becomes challenging. By assuming time as an effective parameter on… (More)
Patent prior art queries are full patent applications which are much longer than standard web search topics. Such queries are composed of hundreds of terms and do not represent a focused information need. One way to make the queries more focused is to select a group of key terms as representatives. Existing works show that such a selection to reduce patent… (More)
This paper addresses the blog distillation problem, that is, given a user query find the blogs that are most related to the query topic. We model each post as evidence of the relevance of a blog to the query, and use aggregation methods like Ordered Weighted Averaging operators to combine the evidence. We show that using only highly relevant evidence… (More)
The goal of a blog distillation (blog feed search) method is to rank blogs according to their recurrent relevance to the query. An interesting property of blog distillation which differentiates it from traditional retrieval tasks is its dependency on time. In this paper we investigate the effect of time dependency in query expansion. We propose a framework,… (More)
Retrieving topically-relevant text passages in documents has been studied many times, but finding non-factoid, multiple sentence answers to web queries is a different task that is becoming increasingly important for applications such as mobile search. As the first stage of developing retrieval models for "answer passages", we describe the process of… (More)
We report on the University of Lugano’s participation in the Blog and Session tracks of TREC 2010. In particular we describe our system for performing blog distillation, faceted search, top stories identification and session reranking.
We report on the University of Lugano’s participation in the Blog track of TREC 2008. In particular we describe our system for performing opinion retrieval and blog distillation.
This paper addresses the blog distillation problem. That is, given a user query find the blogs most related to the query topic. We model the blogosphere as a single graph that includes extra information besides the content of the posts. By performing a random walk on this graph we extract most relevant blogs for each query. Our experiments on the TREC'07… (More)
Passage-based retrieval models have been studied for some time and have been shown to have some benefits for document ranking. Finding passages that are not only topically relevant, but are also answers to the users' questions would have a significant impact in applications such as mobile search. To develop models for answer passage retrieval, we need to… (More)