kNN, Rocchio and Metrics for Information Filtering at TREC-10
نویسندگان
چکیده
منابع مشابه
Recommending Points-of-Interest via Weighted kNN, Rated Rocchio, and Borda Count Fusion
We present the work of the Democritus University of Thrace (DUTH) team in TREC’s 2016 Contextual Suggestion Track. The goal of the Contextual Suggestion Track is to build a system capable of proposing venues which a user might be interested to visit, using any available contextual and personal information. First, we enrich the TREC-provided dataset by collecting more information on venues from ...
متن کاملYFilter at TREC-9
We built a filtering system YFILTER this year, which we used for experiments on profile updating and thresholds setting. Our focus is using incremental Rocchio for introducing new query terms and term weighting. Although 1, 0.5, 0.25 is a widely used Rocchio ratio for query expansion based on relevance feedback, we found that the optimal setting for information filtering is corpus and profile d...
متن کاملThe Bias Problem and Language Models in Adaptive Filtering
We used the YFILTER filtering system for experiments on updating profiles and setting thresholds. We developed a new method of using language models for updating profiles that is more focused on picking informative/discriminative words for query. The new method was compared with the well-known Rocchio algorithm. Dissemination thresholds were set based on maximum likelihood estimation that model...
متن کاملRutgers Filtering Work at TREC 2002: Adaptive and Batch
This year at TREC 2002 we participated in the adaptive filtering sub-task of the filtering track with some models for training a Rocchio classifier. Results were poorer than average on the utility type measures. Using simple feature selection produced better than average results on an F-type measure. The key to our approach was the use of pseudojudgments, and an approach to threshold updating. ...
متن کاملSequential Classifiers Combination for Text Categorization: An Experimental Study
In this paper, we introduce Sequential Classifiers Combination (SCC) into text categorization to improve both the classification effectiveness and classification efficiency of the combined individual classifiers. We apply two classifiers sequentially for experimental study, where the first classifier (called filtering classifier) is used to generate candidate categories for the test document an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001