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Cumulated Gain-based Evaluation of IR Techniques

by Kalervo Järvelin, Jaana Kekäläinen - ACM Transactions on Information Systems , 2002
"... Modem large retrieval environments tend to overwhelm their users by their large output. Since all documents are not of equal relevance to their users, highly relevant documents should be identified and ranked first for presentation to the users. In order to develop IR techniques to this direction, i ..."
Abstract - Cited by 656 (3 self) - Add to MetaCart
. Alternatively, novel measures based on graded relevance assessments may be developed. This paper proposes three novel measures that compute the cumulative gain the user obtains by examining the retrieval result up to a given ranked position. The first one accumulates the relevance scores of retrieved documents

Empirical Justification of the Gain and Discount Function for nDCG

by Evangelos Kanoulas, Javed A. Aslam
"... The nDCG measure has proven to be a popular measure of retrieval effectiveness utilizing graded relevance judgments. However, a number of different instantiations of nDCG exist, depending on the arbitrary definition of the gain and discount functions used (1) to dictate the relative value of documen ..."
Abstract - Cited by 13 (2 self) - Add to MetaCart
of documents of different relevance grades and (2) to weight the importance of gain values at different ranks, respectively. In this work we discuss how to empirically derive a gain and discount function that optimizes the efficiency or stability of nDCG. First, we describe a variance decomposition analysis

Planning Algorithms

by Steven M LaValle , 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
Abstract - Cited by 1108 (51 self) - Add to MetaCart
This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning

IR evaluation methods for retrieving highly relevant documents

by Kalervo Järvelin, Jaana Kekäläinen , 2000
"... This paper proposes evaluation methods based on the use of non-dichotomous relevance judgements in IR experiments. It is argued that evaluation methods should credit IR methods for their ability to retrieve highly relevant documents. This is desirable from the user point of view in moderu large IR e ..."
Abstract - Cited by 400 (4 self) - Add to MetaCart
environments. The proposed methods are (1) a novel application of P-R curves and average precision computations based on separate recall bases for documents of different degrees of relevance, and (2) two novel measures computing the cumulative gain the user obtains by examining the retrieval result up to a

Beyond DCG � User Behavior as a Predictor of a Successful Search

by Ahmed Hassan, Rosie Jones, Kristina Lisa Klinkner
"... Web search engines are traditionally evaluated in terms of the relevance of web pages to individual queries. However, relevance of web pages does not tell the complete picture, since an individual query may represent only a piece of the user’s information need and users may have different informatio ..."
Abstract - Cited by 54 (14 self) - Add to MetaCart
Web search engines are traditionally evaluated in terms of the relevance of web pages to individual queries. However, relevance of web pages does not tell the complete picture, since an individual query may represent only a piece of the user’s information need and users may have different

Personalizing search via automated analysis of interests and activities

by Jaime Teevan , 2005
"... We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than relying on the unrealistic assumption that people will precisely specify their intent when searching, we pursue techniques that ..."
Abstract - Cited by 289 (27 self) - Add to MetaCart
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than relying on the unrealistic assumption that people will precisely specify their intent when searching, we pursue techniques

1 Learning the Gain Values and Discount Factors of Discounted Cumulative Gains

by Ke Zhou, Hongyuan Zha, Yi Chang, Gui-rong Xue
"... Abstract—Evaluation metric is an essential and integral part of a ranking system. In the past several evaluation metrics have been proposed in information retrieval and Web search, among them Discounted Cumulative Gain (DCG) has emerged as one that is widely adopted for evaluating the performance of ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
the performance of ranking functions using DCG very much depends on the particular gain values and discount factors used. We then propose a novel methodology that can learn the gain values and discount factors from user preferences over rankings, modeled as a special case of learning linear utility functions. We

Diversifying Search Results

by Rakesh Agrawal, Alan Halverson , 2009
"... We study the problem of answering ambiguous web queries in a setting where there exists a taxonomy of information, and that both queries and documents may belong to more than one category according to this taxonomy. We present a systematic approach to diversifying results that aims to minimize the r ..."
Abstract - Cited by 276 (5 self) - Add to MetaCart
the risk of dissatisfaction of the average user. We propose an algorithm that well approximates this objective in general, and is provably optimal for a natural special case. Furthermore, we generalize several classical IR metrics, including NDCG, MRR, and MAP, to explicitly account for the value

Modeling User Variance in Time-Biased Gain

by Mark D. Smucker, Charles L. A. Clarke
"... Cranfield-style information retrieval evaluation considers variance in user information needs by evaluating retrieval systems over a set of search topics. For each search topic, traditional metrics model all users searching ranked lists in exactly the same manner and thus have zero variance in their ..."
Abstract - Cited by 8 (2 self) - Add to MetaCart
difference is high, the effect on user experience will be low. Time-biased gain is an evaluation metric that models user interaction with ranked lists that are displayed using document surrogates. In this paper, we extend the stochastic simulation of time-biased gain to model the variation between users. We

Mining interesting locations and travel sequences from gps trajectories

by Yu Zheng, Lizhu Zhang, Xing Xie, Wei-ying Ma - In Proc. of 2009 Int. World Wide Web Conf. (WWW’09 , 2009
"... The increasing availability of GPS-enabled devices is changing the way people interact with the Web, and brings us a large amount of GPS trajectories representing people’s location histories. In this paper, based on multiple users ’ GPS trajectories, we aim to mine interesting locations and classica ..."
Abstract - Cited by 168 (17 self) - Add to MetaCart
The increasing availability of GPS-enabled devices is changing the way people interact with the Web, and brings us a large amount of GPS trajectories representing people’s location histories. In this paper, based on multiple users ’ GPS trajectories, we aim to mine interesting locations
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