Search (8 results, page 1 of 1)

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Abstract

Human information-seeking behavior is a topic of increasing interest in many disciplines. However, the dynamics of this behavior remain elusive. The extant research has taken cognitive and behavioral perspectives to study information-seeking behavior, and observed its dynamics in multiple sessions. However, the underlying mechanisms that govern the dynamics of information-seeking behavior are not well understood. With a focus on interactive information retrieval behavior, this study proposes an integrated framework based on activity theory. This framework is not only comprehensive and integrated, but also offers an explanation of the mechanisms governing the interaction between users' cognitive states and their manifested behavior when using an information retrieval system. A set of four propositions are advanced to describe the mechanisms. The implications are discussed.

Date

27. 5.2007 13:55:22

Type

a

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Abstract

The information science research community is characterized by a paradigm split, with a system-centered cluster working on information retrieval (IR) algorithms and a user-centered cluster working on user behavior. The two clusters rarely leverage each other's insight and strength. One major suggestion from user-centered studies is to treat the relevance judgment of documents as a subjective, multidimensional, and dynamic concept rather than treating it as objective and based on topicality only. This study explores the possibility to enhance users' topicality-based relevance judgment with subjective novelty judgment in interactive IR. A set of systems is developed which differs in the way the novelty judgment is incorporated. In particular, this study compares systems which assume that users' novelty judgment is directed to a certain subtopic area and those which assume that users' novelty judgment is undirected. This study also compares systems which assume that users judge a document based on topicality first and then novelty in a stepwise, noncompensatory fashion and those which assume that users consider topicality and novelty simultaneously and as compensatory to each other. The user study shows that systems assuming directed novelty in general have higher relevance precision, but systems assuming a stepwise judgment process and systems assuming a compensatory judgment process are not significantly different.

Type

a

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Abstract

Human information-seeking behavior is complicated. Activity theory is a powerful theoretical instrument to untangle the "complications." Based on activity theory, a comprehensive framework is proposed in Part I (Y. Xu, 2007) of this report to describe interactive information retrieval (IIR) behavior. A set of propositions is also proposed to describe the mechanisms governing users' cognitive activity and the interaction between users' cognitive states and manifested retrieval behavior. An empirical study is carried out to verify the propositions. The authors' experimental simulation of 81 participants in one search session indicates the propositions are largely supported. Their findings indicate IIR behavior is planned. Users adopt a divide-and-conquer strategy in information retrieval. The planning of information retrieval activity is also partially manifested in query revision tactics. Users learn from previously read documents. A user's interaction with a system ultimately changes the user's information need and the resulting relevance judgment, but the dynamics of topicality perception and novelty perception occur at different paces.

Type

a

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Abstract

The order effect of relevance judgment refers to the different relevance perceptions of a document when it appears in different positions in a list. Although the order effect of relevance judgment has significant theoretical and practical implications, the extant literature is inconclusive regarding its existence and forming mechanisms. This study proposes a set of order effect forming mechanisms, including the learning effect, the subneed scheduling effect, and the cursoriness effect based on the conceptualization of dynamic relevance and the psychology of cognitive elaboration. Our empirical study indicates that in an interactive information retrieval setting, when a document list is reasonably long, order effects demonstrate a curvilinear pattern that conforms to the combined effect of the three mechanisms. Moreover, the curvilinear pattern of order effect could differ for documents of different relevance levels.

Type

a

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Abstract

Knowledge organization (KO) is an interdisciplinary issue which includes some problems in knowledge classification such as how to classify newly emerged knowledge. With the great complexity and ambiguity of knowledge, it is becoming sometimes inefficient to classify knowledge by logical reasoning. This paper attempts to propose a statistical approach to knowledge organization in order to resolve the problems in classifying complex and mass knowledge. By integrating the classification process into a mathematical model, a knowledge classifier, based on the maximum entropy theory, is constructed and the experimental results show that the classification results acquired from the classifier are reliable. The approach proposed in this paper is quite formal and is not dependent on specific contexts, so it could easily be adapted to the use of knowledge classification in other domains within KO.

Type

a

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Abstract

Learning non-taxonomic relations becomes an important research topic in ontology extension. Most of the existing learning approaches are mainly based on expert crafted corpora. These approaches are normally domain-specific and the corpora acquisition is laborious and costly. On the other hand, based on the static corpora, it is not able to meet personalized needs of semantic relations discovery for various taxonomies. In this paper, we propose a novel approach for learning non-taxonomic relations on demand. For any supplied taxonomy, it can focus on the segment of the taxonomy and collect information dynamically about the taxonomic concepts by using Wikipedia as a learning source. Based on the newly generated corpus, non-taxonomic relations are acquired through three steps: a) semantic relatedness detection; b) relations extraction between concepts; and c) relations generalization within a hierarchy. The proposed approach is evaluated on three different predefined taxonomies and the experimental results show that it is effective in capturing non-taxonomic relations as needed and has good potential for the ontology extension on demand.

Type

a

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Abstract

Research in information science now regards users' relevance judgment as subjective perception. However, user-centered studies in the extant literature mainly focus on relevance judgment in problem solving contexts in which the situational relevance of a document is the main concern for users. This study investigates users' relevance judgment in non-problem-solving contexts, i.e., when users search information for epistemic value or entertainment. It is posited that informative relevance and affective relevance should be the main concerns for users. Based on H. P. Grice's (1975, 1989) communication theory and Y. Xu and Z. Chen's (2006) framework, this study tests the significance of topicality, novelty, reliability, understandability, and scope to informative relevance and affective relevance in nonproblem-solving contexts. This empirical study finds novelty, reliability, and topicality to be key aspects of informative relevance.

Type

a

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Type

a