• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.113-133
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• 2012

This study is an exploratory research on the user relevance criteria in Korean search service environments that provide integrated search results. Data were collected from 10 participants using a semi-structured interview technique. The participants conducted a web search using integrated search services, such as Naver or Daum on a self-selected topic. They were asked to judge the relevance of retrieved documents and to report their relevance criteria. As a result, the research indicated 8 user-defined relevance and non-relevance criteria. The research shows that specificity and richness are the two most important criteria yet, the user's relevance criteria have not changed much despite the change in search environment.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.489-500
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• 2009

This research takes a user-centered approach to define relevance, the core concept in information retrieval. The literature on relevance has identified numerous factors affecting such a judgment. We examined the model of user relevance judgment that describes the relationship between user relevance criteria and different types of relevance with information search task. We consider 7 criteria of user relevance-topicality, novelty, reliability, understandability, specificity, richness, and interest-and 3 type of user relevance-cognitive relevance, situational relevance, and affective relevance. Data were collected from a semi-controlled survey and analyzed by a structural equation modeling. As a result, topicality and reliability were found to be the essential relevance criteria in all information retrieval tasks. In the fact search task, topicality, reliability, novelty, richness, and interest were found to be significant. In the problem solving search task, topicality, reliability, understandability, and specificity were found to be significant. In the decision making search task, topicality, reliability, novelty, understandability, richness, specificity, and interest were found to be significant. In addition, the relationships between types of user relevance were determined. This research made theoretical and practical contributions to the field of information retrieval by identifying a definite model of user relevance judgment.

• Journal of Information Science Theory and Practice
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• v.1 no.2
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• pp.16-35
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• 2013

Relevance has a long history of scholarly investigation and discussion in information science. One of its notable concepts is that of 'user-based' relevance. The purpose of this study is to examine how users construct their perspective on the concept of relevance; to analyze what the constituent elements (facets) of relevance are, in terms of core-periphery status; and to compare the difference of constructions of two groups of users (information users vs. information professionals) as applied with a social representations theory perspective. Data were collected from 244 information users and 123 information professionals through use of a free word association method. Three methods were employed to analyze data: (1) content analysis was used to elicit 26 categories (facets) of the concept of relevance; (2) structural analysis of social representations was used to determine the core-periphery status of those facets in terms of coreness, sum of similarity, and weighted frequency; and, (3) maximum tree analysis was used to present and compare the differences between the two groups. Elicited categories in this study overlap with the ones from previous relevance studies, while the findings of a core-periphery analysis show that Topicality, User-needs, Reliability/Credibility, and Importance are configured as core concepts for the information user group, while Topicality, User-needs, Reliability/Credibility, and Currency are core concepts for the information professional group. Differences between the social representations of relevance revealed that Topicality was similar to User-needs and to Importance. Author is closely related to Title while Reliability/Credibility is linked with Currency. Easiness/Clarity is similar to Accuracy. Overall, information users and professionals function with a similar social collective of shared meanings for the concept of relevance. The overall findings identify the core and periphery concepts of relevance and their relationships in terms of coreness, similarity, and weighted frequency.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.3
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• pp.55-70
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• 2014

Although a significant number of studies have been conducted in user-based relevance criteria, a need for further research still remains. The rational is associated with the following inadequacies: (1) research on young user groups, (2) research on the Web environment with multimedia resources, (3) research on the irrelevance criteria and implications to improve related systems and services. Accordingly, this study identified user - based relevance and irrelevance criteria, examining 40 middle school third grader students who use KERIS Edunet site. The results identified 16 relevance criteria and 8 irrelevance criteria. Major implications related to information system and service improvements.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1306-1313
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• 2005

Relevance Feedback(RF), a method to use perceptual feedback in image retrieval, refines a query by the relevance information from a user. However, the user's feedback information is thrown away as soon as a search session ends. So, this paper proposes an enhanced version of RF, which is designed to accumulate human perceptual responses over time through relevance feedback and to dynamically combine the accumulated high-level relevance information with low-level features to further improve the retrieval effectiveness. Experimental results are presented to prove the potential of the proposed RF.

• Journal of the Semiconductor & Display Technology
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• v.7 no.4
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• pp.13-18
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• 2008

This paper explores a content-based image retrieval framework with relevance feedback based on genetic algorithm (GA). This framework adopts GA to learn the user preferences using the similarity functions defined for all available descriptors. The objective of the GA-based learning methods is to learn the user preferences using the similarity functions and to find a descriptor combination function that best represents the user perception. Experiments were performed to validate the proposed frameworks. The experiments employed the natural image databases and color and texture descriptors to represent the content of database images. The proposed frameworks were compared with the other two relevance feedback methods regarding effectiveness in image retrieval tasks. Experiment results demonstrate the superiority of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.754-759
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• 2007

The information recommendation system offers selected documents according to information needs of dynamic users. User's needs are expressed as profiles consisting of one or more words and may be changed into some specifics through relevance feedback made by users during the recommendation process. In previous research, users have entered relevance information by taking part in explicit relevance feedbacks and learned user profiles using the positive relevance feedbacks. In this paper, we learn user profiles using not only positive relevance feedback but negative relevance feedback and reinforcement learning. To compare the proposed with previous method, we performed experiments to evaluate recommendation performance of the same topic. As a result, the former shows the improved performance than the latter does.

• Journal of the Korean Society for Library and Information Science
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• v.35 no.3
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• pp.173-189
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• 2001

This paper presents a framework for observable behavior that can be used as a basis for user modeling, and it reports the results of a pair of user studies that examine the joint utility of two specific behaviors. User models can be constructed by hand, or they can be teamed automatically based on feedback provided by the user about the relevance of documents that they have examined. By observing user behavior, it is possible to obtain implicit feedback without requiring explicit relevance judgments. Four broad categories of potentially observable behavior are identified : examine, retain, reference, and annotate, and examples of specific behaviors within a category are further subdivided based on the natural scope of information objects being manipulated . segment object, or class. Previous studies using Internet discussion groups (USENET news) have shown reading time to be a useful source of implicit feedback for predicting a user's preferences. The experiments reported in this paper extend that work to academic and professional journal articles and abstracts, and explore the relationship between printing behavior and reading time. Two user studies were conducted in which undergraduate students examined articles or abstracts from the telecommunications or pharmaceutical literature. The results showed that reading time can be used to predict the user's assessment of relevance, that the mean reading time for journal articles and technical abstracts is longer than has been reported for USENET news documents, and that printing events provide additional useful evidence about relevance beyond that which can be inferred from reading time. The paper concludes with a brief discussion of the implications of the reported results.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.211-229
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• 2022

In this study, we aimed to define the effects of anthropomorphism and conversational relevance of chatbots on user experience. In specific, the chatbot designed for this study was an online shopping assistant that recommends items for consumers. Levels of anthropomorphism was manipulated by the name, profile picture, word choices, and emojis, while conversational relevance was adjusted by the depth and accuracy of the recommendation. Three categories of user experience were measured: psychological distance, usability, and purchase intentions. The results implied a significant main effect of conversational relevance on all variables for the high anthropomorphized conditions, while all but psychological distance was significant for low anthropomorphized conditions. Although there was no significant main effect of anthropomorphism observed for the variables, the main effect of anthropomorphism on responsibility was marginally significant for a specific item. The results of this study may function as a guidance for future studies regarding usage of chatbots within a marketing setting.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.238-240
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• 2002

If there is an Information Retrieval system which comprehends the semantic content of documents and knows the preference of users. the system can search the information better on the Internet, or improve the IR performance. Therefore we propose the IR model which combines semantic based indexing and fuzzy relevance model. In addition to the statistical approach, we chose the semantic approach in indexing, lexical chains, because we assume it would improve the performance of the index term extraction. Furthermore, we combined the semantic based indexing with the fuzzy model, which finds out the exact relevance of the user preference and index terms. The proposed system works as follows: First, the presented system indexes documents by the efficient index term extraction method using lexical chains. And then, if a user tends to retrieve the information from the indexed document collection, the extended IR model calculates and ranks the relevance of user query. user preference and index terms by some metrics. When we experimented each module, semantic based indexing and extended fuzzy model. it gave noticeable results. The combination of these modules is expected to improve the information retrieval performance.