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C.: Extending the Rocchio Relevance Feedback Algorithm to Provide Contextual Retrieval

by Chris Jordan, Carolyn Watters - In the Proceedings of AWIC04. (2004) 135–144
"... Abstract. Contextual retrieval supports differences amongst users in their information seeking requests. The Web, which is very dynamic and nearly universally accessible, is an environment in which it is increasingly difficult for users to find documents that satisfy their specific information needs ..."
Abstract - Cited by 3 (1 self) - Add to MetaCart
needs. This problem is amplified as users tend to use short queries. Contextual retrieval attempts to address this problem by incorporating knowledge about the user and past retrieval results in the search process. In this paper we explore a feedback technique based on the Rocchio algorithm

Extending the Rocchio Relevance Feedback Algorithm to Provide Contextual Retrieval

by unknown authors
"... Abstract. Contextual retrieval supports differences amongst users in their information seeking requests. The Web, which is very dynamic and nearly universally accessible, is an environment in which it is increasingly difficult for users to find documents that satisfy their specific information needs ..."
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needs. This problem is amplified as users tend to use short queries. Contextual retrieval attempts to address this problem by incorporating knowledge about the user and past retrieval results in the search process. In this paper we explore a feedback technique based on the Rocchio algorithm

A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization

by Thorsten Joachims , 1997
"... The Rocchio relevance feedback algorithm is one of the most popular and widely applied learning methods from information retrieval. Here, a probabilistic analysis of this algorithm is presented in a text categorization framework. The analysis gives theoretical insight into the heuristics used in the ..."
Abstract - Cited by 456 (1 self) - Add to MetaCart
The Rocchio relevance feedback algorithm is one of the most popular and widely applied learning methods from information retrieval. Here, a probabilistic analysis of this algorithm is presented in a text categorization framework. The analysis gives theoretical insight into the heuristics used

Rocchio: Relevance Feedback in Learning Classification Algorithms

by Mark Van Uden
"... Given a large amount of documents it is hard to find the documents that you need. These days most-if not all- of these documents are available electronically. Information Retrieval (IR) systems help in finding the documents that satisfy the user's information need. There are many techniques tha ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
that are used by these IR systems. One of these techniques is learning classification. This technique uses preclassified training documents for classification of documents in the document base. Rocchio is one of these learning classification algorithms. In this article test data are used to compare Rocchio

Support vector machine active learning for image retrieval

by Simon Tong , 2001
"... Relevance feedback is often a critical component when designing image databases. With these databases it is difficult to specify queries directly and explicitly. Relevance feedback interactively determinines a user’s desired output or query concept by asking the user whether certain proposed images ..."
Abstract - Cited by 456 (28 self) - Add to MetaCart
are relevant or not. For a relevance feedback algorithm to be effective, it must grasp a user’s query concept accurately and quickly, while also only asking the user to label a small number of images. We propose the use of a support vector machine active learning algorithm for conducting effective relevance

On the complexity of Rocchio’s similarity-based relevance feedback algorithm

by Zhixiang Chen, Bin Fu - Journal of the American Society for Information Science and Technology, Accepted , 2005
"... Rocchio's similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive learning algorithm from examples in searching for documents represented by a linear classifier. In spite of its popularity in various ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Rocchio's similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive learning algorithm from examples in searching for documents represented by a linear classifier. In spite of its popularity

Boosting and Rocchio Applied to Text Filtering

by Robert E. Schapire, Yoram Singer, Amit Singhal - In Proceedings of ACM SIGIR , 1998
"... We discuss two learning algorithms for text filtering: modified Rocchio and a boosting algorithm called AdaBoost. We show how both algorithms can be adapted to maximize any general utility matrix that associates cost (or gain) for each pair of machine prediction and correct label. We first show that ..."
Abstract - Cited by 113 (2 self) - Add to MetaCart
We discuss two learning algorithms for text filtering: modified Rocchio and a boosting algorithm called AdaBoost. We show how both algorithms can be adapted to maximize any general utility matrix that associates cost (or gain) for each pair of machine prediction and correct label. We first show

Some Formal Analysis of Rocchio's Similarity-Based Relevance Feedback Algorithm

by Zhixiang Chen, Binhai Zhu - Information Retrieval , 2000
"... Rocchio's similarity-based Relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised learning algorithm from examples. ..."
Abstract - Cited by 16 (7 self) - Add to MetaCart
Rocchio's similarity-based Relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised learning algorithm from examples.

A Quadratic Lower Bound for Rocchio’s Similarity-Based Relevance Feedback Algorithm

by Zhixiang Chen, Bin Fu, John Abraham - Proceedings of the Seventh Annual International Computing and Combinatorics Conference, LNCS 3595 , 2005
"... Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised learning algorithm from examples. In practice, Rocchio’s algorithm often uses a fixed query updating factor. When this is the c ..."
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Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised learning algorithm from examples. In practice, Rocchio’s algorithm often uses a fixed query updating factor. When

Training Algorithms for Linear Text Classifiers

by David Lewis, Robert E. Schapire, James P. Callan, Ron Papka , 1996
"... Systems for text retrieval, routing, categorization and other IR tasks rely heavily on linear classifiers. We propose that two machine learning algorithms, the Widrow-Hoff and EG algorithms, be used in training linear text classifiers. In contrast to most IR methods, theoretical analysis provides pe ..."
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performance guarantees and guidance on parameter settings for these algorithms. Experimental data is presented showing Widrow-Hoff and EG to be more effective than the widely used Rocchio algorithm on several categorization and routing tasks. 1 Introduction Document retrieval, categorization, routing
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