Relevance Feedback Based on Constrained Clustering: FDU at TREC 09
نویسندگان
چکیده
We introduce our participation of the TREC Relevance Feedback(RF) TRACK in 2009. The RF09 TRACK is focused on the explicit relevant feedback, where a few relevant and irrelevant documents are available to each query. Our system is implemented under the framework of probabilistic language model. We apply the constrained clustering on the top returned documents and extract the expanded words to reform the query. We also extract the named entities from the explicit relevant documents to expand the query. The experiment was conducted on the ClueWeb09 TREC Category B, which is a new and huge test collection for the TREC TRACKs. The evaluation result shows the performance of the constrained clustering.
منابع مشابه
FDU at TREC 2007: Opinion Retrieval of Blog Track
This paper describes our participation in the opinion retrieval task at Blog Track 07. The system consisted of the preprocess part, the topic retrieval part and sentiment analysis part. In the topic retrieval part, we adopted pseudo-relevance feedback and a novel approach to form a modified query. In the sentiment analysis part, each blog post was given an opinion score based on the sentences c...
متن کاملUCSC at Relevance Feedback Track
The relevance feedback track in TREC 2009 focuses on two sub tasks: actively selecting good documents for users to provide relevance feedback and retrieving documents based on user relevance feedback. For the first task, we tried a clustering based method and the Transductive Experimental Design (TED) method proposed by Yu et al. [5]. For clustering based method, we use the K-means algorithm to...
متن کاملCMIC@TREC 2009: Relevance Feedback Track
This paper describes CMIC’s submissions to the TREC’09 relevance feedback track. In the phase 1 runs we submitted, we experimented with two different techniques to produce 5 documents to be judged by the user in the initial feedback step, namely using knowledge bases and clustering. Both techniques attempt to topically diversify these 5 documents as much as possible in an effort to maximize the...
متن کاملCluster-Based Relevance Feedback: Legal Track 2011
This is our second participation in the TREC Legal Track. The TREC Legal Track 2011 featured only the Learning Task. We participated in Topics 401 and 403. We used Lemur 4.11 for Boolean retrieval and followed it with a clustering technique, where we chose members from each cluster (which we called seeds) for relevance judgement by the TA and assumed all other members of the cluster whose seeds...
متن کاملFDU at TREC-9: CLIR, Filtering and QA Tasks
This year Fudan University takes part in the TREC-9 conference for the first time. We have participated in three tracks of CLIR, Filtering and QA. We have submitted four runs for CLIR track. Bilingual knowledge source and statistical-based search engine are integrated in our CLIR system. We varied our strategy somewhat between runs: long query (both title and description field of the queries in...
متن کامل