Abstract One of the challenges of modern information retrieval is to rank the most relevant documents at the top of the large system output. This calls for choosing the proper methods to evaluate the system performance. The traditional performance measures, such as precision and recall, are based on binary relevance judgment and are not appropriate for multi-grade relevance. The main objective of this paper is to propose a framework for system evaluation based on user preference of documents. It is shown that the notion of user preference is general and flexible for formally defining and interpreting multi-grade relevance. We review 12 evaluation methods and compare their similarities and differences. We find that the normalized distance pe...
© 2011 Dr. Sri Devi RavanaComparative evaluations of information retrieval systems using test collec...
The variety of performance measures available for infor-mation retrieval systems, search engines, an...
Research in Information Retrieval has progressed against a background of rapidly increasing corpus s...
The information retrieval system evaluation is necessary to measure and quantify the effectiveness,...
In this paper we present some new methods of ranking information retrieval systems without relevance...
In this paper we present some new methods of ranking information retrieval systems without relevance...
In this paper we present some new methods of ranking information retrieval systems without relevance...
Some measures such as mean average precision and recall level precision are considered as good syste...
Some measures such as mean average precision and recall level precision are considered as good syste...
Some measures such as mean average precision and recall level precision are considered as good syste...
Purpose: The effort in addition to relevance is a major factor for satisfaction and utility of the d...
© 2010 Dr. William Edward WebberFull-text retrieval systems employ heuristics to match documents to ...
Evaluation of information retrieval (IR) systems has recently been exploring the use of preference j...
Large-scale retrieval systems are often implemented as a cascading sequence of phases-a first filter...
Large-scale retrieval systems are often implemented as a cascading sequence of phases-a first filter...
© 2011 Dr. Sri Devi RavanaComparative evaluations of information retrieval systems using test collec...
The variety of performance measures available for infor-mation retrieval systems, search engines, an...
Research in Information Retrieval has progressed against a background of rapidly increasing corpus s...
The information retrieval system evaluation is necessary to measure and quantify the effectiveness,...
In this paper we present some new methods of ranking information retrieval systems without relevance...
In this paper we present some new methods of ranking information retrieval systems without relevance...
In this paper we present some new methods of ranking information retrieval systems without relevance...
Some measures such as mean average precision and recall level precision are considered as good syste...
Some measures such as mean average precision and recall level precision are considered as good syste...
Some measures such as mean average precision and recall level precision are considered as good syste...
Purpose: The effort in addition to relevance is a major factor for satisfaction and utility of the d...
© 2010 Dr. William Edward WebberFull-text retrieval systems employ heuristics to match documents to ...
Evaluation of information retrieval (IR) systems has recently been exploring the use of preference j...
Large-scale retrieval systems are often implemented as a cascading sequence of phases-a first filter...
Large-scale retrieval systems are often implemented as a cascading sequence of phases-a first filter...
© 2011 Dr. Sri Devi RavanaComparative evaluations of information retrieval systems using test collec...
The variety of performance measures available for infor-mation retrieval systems, search engines, an...
Research in Information Retrieval has progressed against a background of rapidly increasing corpus s...