A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Bridging the Gap: A Genre Analysis of Weblogs
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
Discriminative models for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A Self-Organizing Search Engine for RSS Syndicated Web Contents
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
A regression framework for learning ranking functions using relative relevance judgments
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A framework for projected clustering of high dimensional data streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Detecting splogs via temporal dynamics using self-similarity analysis
ACM Transactions on the Web (TWEB)
Retrieval and feedback models for blog feed search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Key blog distillation: ranking aggregates
Proceedings of the 17th ACM conference on Information and knowledge management
Blog site search using resource selection
Proceedings of the 17th ACM conference on Information and knowledge management
Search Engines: Information Retrieval in Practice
Search Engines: Information Retrieval in Practice
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting spam blogs: a machine learning approach
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Semantic-based Merging of RSS Items
World Wide Web
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
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Feed has become a popular way to effectively distribute and acquire information on the web. The explosive growth of feeds demands a search engine that can help users quickly discover feeds of their interests. Retrieval effectiveness of feed search engine highly depends on a relevance assessment method that determines candidates for ranking query results. However, existing relevance assessment approaches proposed for web page retrieval may produce unsatisfactory result due to the different characteristics of feeds from traditional web pages. Compared to web pages, feed is a dynamic document since it continually generates information on some specific topics. In addition, it is a structured document that consists of several data elements such as title and description. Accordingly, the relevance assessment method for feed retrieval needs to effectively address these unique characteristics of feeds. This paper considers a problem of identifying significant features which are a feature set created from feed data elements, with the aim of improving effectiveness of feed retrieval while at the same time reducing computational cost. We conducted extensive experiments to investigate the problem using support vector machine on real-world data sets, and found the significant features that can be employed for feed search services.