Cognitive Agents for Web Based Search Engines: A Review
01 Feb 2017-pp 201-206
TL;DR: The goal is to enhance the search experience by fewer repetitions of queries and making it easier for the users to retrieve the highly relevant documents of their interest.
Abstract: Search Engine (SE) is the most used information retrieval tool in the present scenario. In spite of the huge involvement of users in search engines, their limited capabilities to understand the user context and emotions places high load on the user to maintain the search momentum. Thus the research is being done on the web search process including the users. The aim is to reduce the contextual and emotional mismatch between the SE's and users. Personalized user query processing, current knowledge updation on users, information retrieval effectiveness and user satisfaction are the major challenges to be addressed in this field. To meet the high level requirements of the users and to improve the intellectualization level of the search, various cognitive agent based SE models are proposed in the literature. The challenges of the cognitive agents in present search engine scenario are obtaining sufficient percepts from the environment, understanding it, gathering the knowledge and retrieving the information from the huge volume of data. Recent advancements in the field of semantic search engines, knowledge gathering techniques and information retrieval methods are discussed which can better the cognitive agent based search engines by addressing the challenges. Overall the goal is to enhance the search experience by fewer repetitions of queries and making it easier for the users to retrieve the highly relevant documents of their interest.
Citations
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13 Aug 2021
10 citations
21 Jan 2020
TL;DR: In this article, the authors discuss the importance of information dissemination in the context of data-driven information dissemination, and propose an information dissemination strategy based on the concept of QoS.
Abstract: Rəqəmsal materiallar fasiləsiz artan, müxtəlif formatlarda təqdim edilən mətn sənədlərindən, verilənlər bazasından, təsvirlərdən, səsli və qrafik materiallardan, proqram təminatı və vebsəhifələrdən ibarətdir. Rəqəmsal informasiyanın sürətli artımı, verilənlərin müxtəlifliyi unikal verilənlər strukturunun vaxtında analiz edilməsi, daha uyğun, dolğun axtarışı və emalı zərurətini yaratmışdır. Bu məqsədlə məqalədə qeyri-ənənəvi verilənlər strukturuna malik böyük verilənlərin emalı zamanı süni intellektə əsaslanan alqoritmlərin xüsusiyyətləri analiz olunmuşdur. Müəyyən edilmişdir ki, axtarışın keyfiyyətinin yaxşılaşdırılması, verilənlərin həcminin böyüklüyü, istifadəçi sorğularının axınının intensivliyi ilə bağlı məsələlərin həlli zamanı süni intellektə əsaslanan alqoritmlərdən istifadə olunması zəruridir. Eyni zamanda məqalədə axtarış alqoritmləri təhlil olunmuş, onların problemləri təsnifatlandırılmış və axtarış sistemlərinin imkanlarının maksimum istifadəsi üçün potensial həllər təklif edilmişdir.
4 citations
Additional excerpts
...[23]-də təkilf olunan metod istifadəçilərin informasiya ehtiyaclarını müəyyənləşdirmək üçün dəqiq olan terminlərin seçilməsində kömək edir....
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25 Jun 2021
TL;DR: This article analysed and discussed the personalized recommendations of searches using a tailored framework that supports search engines and describes a comprehensive review of the study on search engine customization for web-based queries.
Abstract: Mostly with growth of the information sector, in particular the World wide web and the mobile Internet, the volume of information that we’ll have to contend with is rapidly increasing. To a certain degree, users could get the information they need from the Internet. And in context of these vast availability and proliferation of information, users need an efficient way of finding only important and interesting information. How to optimize usability during information search process is still not addressed. Searching was the key feature of a conventional search engine. There has been insufficient customization in search engines to be used by searchers during the information extraction process. This article thus analysed and discussed the personalized recommendations of searches using a tailored framework that supports search engines. We describe a comprehensive review of the study on search engine customization for web-based queries. The study is partially systematic and, also at end of the study, we discuss the difficulties of personalizing search engines.
1 citations
26 Nov 2022
TL;DR: In this paper , the authors propose an agent-based approach to document expansion, where agents collect terms from relevant queries and perform topic modeling on these terms and publish different variants expanded with the topic terms to the search index.
Abstract: With the advent of data ecosystems finding information in distributed and federated catalogs and marketplaces becomes more and more important. One of the problems in data search and search in general is the mismatch between the terminology of users and of the searched items, be it dataset metadata or web pages. The paper proposes an agent-based approach to document expansion (ADE). The idea is to represent documents with agents that exploit local information collected from user searches and relevant signals to improve the representation of the document in a search index and subsequently to improve the search performance of the system. The agents collect terms from relevant queries and perform topic modeling on these terms and publish different variants expanded with the topic terms to the search index. We find that the approach achieves good improvement in search performance and is a valuable tool because is places no burden on the information retrieval pipeline and is complementary to other document expansion and information retrieval approaches.
References
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TL;DR: This paper presents a multi-agent based framework for simulating human and social behavior during emergency evacuation, which is able to demonstrate some emergent behaviors, such as competitive, queuing, and herding behaviors.
Abstract: Many computational tools for the simulation and design of emergency evacuation and egress are now available. However, due to the scarcity of human and social behavioral data, these computational tools rely on assumptions that have been found inconsistent or unrealistic. This paper presents a multi-agent based framework for simulating human and social behavior during emergency evacuation. A prototype system has been developed, which is able to demonstrate some emergent behaviors, such as competitive, queuing, and herding behaviors. For illustration, an example application of the system for safe egress design is provided.
478 citations
"Cognitive Agents for Web Based Sear..." refers background or methods in this paper
...Multi Agent Simulation System (MASS) mentioned in [12] is used for progress analysis to observe human behaviour in emergencies....
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...User-Generated Content (UCG) concept is used in [14] to evaluate web information which is shared and has become necessary and important in future [12]....
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...Conditional Random Field (CRF) given in [12] is used to identify emotional expressions....
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Proceedings Article•
26 Oct 2003
TL;DR: Since the preeminent functions of music are social and psychological, the most useful characterization would be based on four types of information: the style, emotion, genre, and similarity.
Abstract: Music is not only for entertainment and for pleasure, but has been used for a wide range of purposes due to its social and physiological effects. Traditionally musical information has been retrieved and/or classified based on standard reference information, such as the name of the composer and the title of the work etc. These basic pieces information will remain essential, but information retrieval based on these are far from satisfactory. Huron points out that since the preeminent functions of music are social and psychological, the most useful characterization would be based on four types of information: the style, emotion, genre, and similarity [Huron,2000].
294 citations
01 Jan 2001
TL;DR: The authors argue that the available evidence does not show an unambiguous causal relation to emotions, and appraisals appear as consequences of emotions as well as antecedents, and that emotion elicitation depends not only on appraisal but also on prevailing emotional response tendencies and, on occasion, on direct stimulus effects.
Abstract: (from the chapter) Critiques 2 core theses of appraisal theory: (1) appraisal is responsible for the elicitation of emotions, and (2) appraisal is responsible for the differentiation of emotions. The authors argue, first, that much research purporting to provide support for appraisal theory fails to do so by not clearly separating the antecedent, appraisal, from the consequent, emotion. Second, the authors argue that the available evidence does not show an unambiguous causal relation to emotions, and appraisals appear as consequences of emotions as well as antecedents. Third, emotion elicitation depends not only on appraisal but also on prevailing emotional response tendencies and, on occasion, on direct stimulus effects. Appraisals and emotions thus do not stand in such a clear relationship as appraisal theory would suggest. Fourth, the authors argue that a more or less complete evaluation of the role of appraisal in emotion elicitation requires extending the domain of dependent variables currently used in this context.
117 citations
"Cognitive Agents for Web Based Sear..." refers background or methods in this paper
...The appraisals are the interpretation of the emotion words used in the analyses [9]....
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...This observation is pointed out by Frijda and Zeelenberg [9] as “action readiness” that is an important result of appraisal....
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TL;DR: This paper proposes a relation-based page rank algorithm to be used in conjunction with semantic Web search engines that simply relies on information that could be extracted from user queries and on annotated resources.
Abstract: With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general-purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming this limitation. Several search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of semantic Web resources, that is, relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper, we propose a relation-based page rank algorithm to be used in conjunction with semantic Web search engines that simply relies on information that could be extracted from user queries and on annotated resources. Relevance is measured as the probability that a retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.
116 citations
"Cognitive Agents for Web Based Sear..." refers background in this paper
...This intern will enhance the efficacy of cognitive agent based Web SE’s....
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...The aim is to reduce the contextual and emotional mismatch between the SEs and the user....
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...Among different types of SE architectures, the relevancy measures precision and recall are enhanced using the intelligent web SEs....
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...The user behaviour model can be employed in cognitive agents to build multi strategy intelligent SE’s in order to improve retrieval effectiveness measure....
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...In semantic web search engines literatures, it is reported that identifying the relationship among the concepts embedded in semantic annotations to inference the user context pose a major challenge to SE’s....
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