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Elovici, Y.; Shapira, Y.B.; Kantor, P.B.: ¬A decision theoretic approach to combining information filters : an analytical and empirical evaluation. (2006) 0.05

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Abstract: The outputs of several information filtering (IF) systems can be combined to improve filtering performance. In this article the authors propose and explore a framework based on the so-called information structure (IS) model, which is frequently used in Information Economics, for combining the output of multiple IF systems according to each user's preferences (profile). The combination seeks to maximize the expected payoff to that user. The authors show analytically that the proposed framework increases users expected payoff from the combined filtering output for any user preferences. An experiment using the TREC-6 test collection confirms the theoretical findings.
Date: 22. 7.2006 15:05:39

Kantor, P.B.: Mathematical models in information science (2002) 0.02

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Source: Bulletin of the American Society for Information Science. 28(2002) no.6, S.22-24

Kantor, P.B.: ¬The logic of weighted queries (1981) 0.02

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Source: IEEE transactions on systems, man and cybernetics. 7(1981) S.816-821

Sun, Y.; Kantor, P.B.; Morse, E.L.: Using cross-evaluation to evaluate interactive QA systems (2011) 0.02
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Abstract

In this article, we report on an experiment to assess the possibility of rigorous evaluation of interactive question-answering (QA) systems using the cross-evaluation method. This method takes into account the effects of tasks and context, and of the users of the systems. Statistical techniques are used to remove these effects, isolating the effect of the system itself. The results show that this approach yields meaningful measurements of the impact of systems on user task performance, using a surprisingly small number of subjects and without relying on predetermined judgments of the quality, or of the relevance of materials. We conclude that the method is indeed effective for comparing end-to-end QA systems, and for comparing interactive systems with high efficiency.

Kantor, P.B.: ¬A model for stopping behavior of the users of on-line systems (1987) 0.02

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Ng, K.B.; Loewenstern, D.; Basu, C.; Hirsh, H.; Kantor, P.B.: Data fusion of machine-learning methods for the TREC5 routing tak (and other work) (1997) 0.02

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Date: 27. 2.1999 20:59:22

Kantor, P.B.: Information retrieval techniques (1994) 0.02
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Abstract

State of the art review of information retrieval techniques viewed in terms of the growing effort to implement concept based retrieval in content based algorithms. Identifies trends in the automation of indexing, retrieval, and the interaction between systems and users. Identifies 3 central issues: ways in which systems describe documents for purposes of information retrieval; ways in which systems compute the degree of match between a given document and the current state of the query; amd what the systems do with the information that they obtain from the users. Looks at information retrieval techniques in terms of: location, navigation; indexing; documents; queries; structures; concepts; matching documents to queries; restoring query structure; algorithms and content versus concepts; formulation of concepts in terms of contents; formulation of concepts with the assistance of the users; complex system codes versus underlying principles; and system evaluation
Shapira, B.; Kantor, P.B.; Melamed, B.: ¬The effect of extrinsic motivation on user behavior in a collaborative information finding system (2001) 0.01
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Abstract

In collaborative information finding systems, evaluations provided by users assist other users with similar needs. This article examines the problem of getting users to provide evaluations, thus overcoming the so-called "free-riding" behavior of users. Free riders are those who use the information provided by others without contributing evaluations of their own. This article reports on an experiment conducted using the "AntWorld," system, a collaborative information finding system for the Internet, to explore the effect of added motivation on users' behavior. The findings suggest that for the system to be effective, users must be motivated either by the environment, or by incentives within the system. The findings suggest that relatively inexpensive extrinsic motivators can produce modest but significant increases in cooperative behavior
Menkov, V.; Ginsparg, P.; Kantor, P.B.: Recommendations and privacy in the arXiv system : a simulation experiment using historical data (2020) 0.01
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Abstract

Recommender systems may accelerate knowledge discovery in many fields. However, their users may be competitors guarding their ideas before publication or for other reasons. We describe a simulation experiment to assess user privacy against targeted attacks, modeling recommendations based on co-access data. The analysis uses an unusually long (14?years) set of anonymized historical data on user-item accesses. We introduce the notions of "visibility" and "discoverability." We find, based on historical data, that the majority of the actions of arXiv users would be potentially "visible" under targeted attack. However, "discoverability," which incorporates the difficulty of actually seeing a "visible" effect, is very much lower for nearly all users. We consider the effect of changes to the settings of the recommender algorithm on the visibility and discoverability of user actions and propose mitigation strategies that reduce both measures of risk.
Sun, Y.; Kantor, P.B.: Cross-evaluation : a new model for information system evaluation (2006) 0.01
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Abstract

In this article, we introduce a new information system evaluation method and report on its application to a collaborative information seeking system, AntWorld. The key innovation of the new method is to use precisely the same group of users who work with the system as judges, a system we call Cross-Evaluation. In the new method, we also propose to assess the system at the level of task completion. The obvious potential limitation of this method is that individuals may be inclined to think more highly of the materials that they themselves have found and are almost certain to think more highly of their own work product than they do of the products built by others. The keys to neutralizing this problem are careful design and a corresponding analytical model based on analysis of variance. We model the several measures of task completion with a linear model of five effects, describing the users who interact with the system, the system used to finish the task, the task itself, the behavior of individuals as judges, and the selfjudgment bias. Our analytical method successfully isolates the effect of each variable. This approach provides a successful model to make concrete the "threerealities" paradigm, which calls for "real tasks," "real users," and "real systems."

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