Web Sites as Agents’ Environments: General Framework and Applications

Author(s):  
Stefania Bandini ◽  
Sara Manzoni ◽  
Giuseppe Vizzari
Keyword(s):  
Web Mining ◽  
2011 ◽  
pp. 276-306 ◽  
Author(s):  
Honghua Dai

Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional approaches such as collaborative filtering. Despite their success, such systems, as in more traditional ones, do not take into account the semantic knowledge about the underlying domain. Without such semantic knowledge, personalization systems cannot recommend different types of complex objects based on their underlying properties and attributes. Nor can these systems possess the ability to automatically explain or reason about the user models or user recommendations. The integration of semantic knowledge is, in fact, the primary challenge for the next generation of personalization systems. In this chapter we provide an overview of approaches for incorporating semantic knowledge into Web usage mining and personalization processes. In particular, we discuss the issues and requirements for successful integration of semantic knowledge from different sources, such as the content and the structure of Web sites for personalization. Finally, we present a general framework for fully integrating domain ontologies with Web usage mining and personalization processes at different stages, including the preprocessing and pattern discovery phases, as well as in the final stage where the discovered patterns are used for personalization.


2008 ◽  
pp. 3557-3585 ◽  
Author(s):  
Honghua Dai ◽  
Bamshad Mobasher

Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional approaches such as collaborative filtering. Despite their success, such systems, as in more traditional ones, do not take into account the semantic knowledge about the underlying domain. Without such semantic knowledge, personalization systems cannot recommend different types of complex objects based on their underlying properties and attributes. Nor can these systems possess the ability to automatically explain or reason about the user models or user recommendations. The integration of semantic knowledge is, in fact, the primary challenge for the next generation of personalization systems. In this chapter we provide an overview of approaches for incorporating semantic knowledge into Web usage mining and personalization processes. In particular, we discuss the issues and requirements for successful integration of semantic knowledge from different sources, such as the content and the structure of Web sites for personalization. Finally, we present a general framework for fully integrating domain ontologies with Web usage mining and personalization processes at different stages, including the preprocessing and pattern discovery phases, as well as in the final stage where the discovered patterns are used for personalization.


2009 ◽  
pp. 732-759 ◽  
Author(s):  
Honghua Dai ◽  
Bamshad Mobasher

Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional approaches such as collaborative filtering. Despite their success, such systems, as in more traditional ones, do not take into account the semantic knowledge about the underlying domain. Without such semantic knowledge, personalization systems cannot recommend different types of complex objects based on their underlying properties and attributes. Nor can these systems possess the ability to automatically explain or reason about the user models or user recommendations. The integration of semantic knowledge is, in fact, the primary challenge for the next generation of personalization systems. In this chapter we provide an overview of approaches for incorporating semantic knowledge into Web usage mining and personalization processes. In particular, we discuss the issues and requirements for successful integration of semantic knowledge from different sources, such as the content and the structure of Web sites for personalization. Finally, we present a general framework for fully integrating domain ontologies with Web usage mining and personalization processes at different stages, including the preprocessing and pattern discovery phases, as well as in the final stage where the discovered patterns are used for personalization.


2011 ◽  
pp. 205-232
Author(s):  
Honghua Dai

Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional approaches such as collaborative filtering. Despite their success, such systems, as in more traditional ones, do not take into account the semantic knowledge about the underlying domain. Without such semantic knowledge, personalization systems cannot recommend different types of complex objects based on their underlying properties and attributes. Nor can these systems possess the ability to automatically explain or reason about the user models or user recommendations. The integration of semantic knowledge is, in fact, the primary challenge for the next generation of personalization systems. In this chapter we provide an overview of approaches for incorporating semantic knowledge into Web usage mining and personalization processes. In particular, we discuss the issues and requirements for successful integration of semantic knowledge from different sources, such as the content and the structure of Web sites for personalization. Finally, we present a general framework for fully integrating domain ontologies with Web usage mining and personalization processes at different stages, including the preprocessing and pattern discovery phases, as well as in the final stage where the discovered patterns are used for personalization.


2001 ◽  
Vol 6 (2) ◽  
pp. 6-8
Author(s):  
Christopher R. Brigham

Abstract The AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), Fifth Edition, explains that independent medical evaluations (IMEs) are not the same as impairment evaluations, and the evaluation must be designed to provide the data to answer the questions asked by the requesting client. This article continues discussions from the September/October issue of The Guides Newsletter and examines what occurs after the examinee arrives in the physician's office. First are orientation and obtaining informed consent, and the examinee must understand that there is no patient–physician relationship and the physician will not provide treatment bur rather will send a report to the client who requested the IME. Many physicians ask the examinee to complete a questionnaire and a series of pain inventories before the interview. Typical elements of a complete history are shown in a table. An equally detailed physical examination follows a meticulous history, and standardized forms for reporting these findings are useful. Pain and functional status inventories may supplement the evaluation, and the examining physician examines radiographic and diagnostic studies. The physician informs the interviewee when the evaluation is complete and, without discussing the findings, asks the examinee to complete a satisfaction survey and reviews the latter to identify and rectify any issues before the examinee leaves. A future article will discuss high-quality IME reports.


1999 ◽  
Vol 4 (6) ◽  
pp. 5-6

Abstract Personality disorders are enduring patterns of inner experience and behavior that deviate markedly from those expected by the individual's culture; these inflexible and pervasive patterns reflect issues with cognition, affectivity, interpersonal functioning and impulse control, and lead to clinically significant distress or impairment in social, occupational, or other important areas of functioning. The AMA Guides to the Evaluation of Permanent Impairment, Fourth Edition, defines two specific personality disorders, in addition to an eleventh condition, Personality Disorder Not Otherwise Specified. Cluster A personality disorders include paranoid, schizoid, and schizotypal personalities; of these, Paranoid Personality Disorder probably is most common in the legal arena. Cluster B personality disorders include antisocial, borderline, histrionic, and narcissistic personality. Such people may suffer from frantic efforts to avoid perceived abandonment, patterns of unstable and intense interpersonal relationships, an identity disturbance, and impulsivity. Legal issues that involve individuals with cluster B personality disorders often involve determination of causation of the person's problems, assessment of claims of harassment, and assessment of the person's fitness for employment. Cluster C personality disorders include avoidant, dependent, and obsessive-compulsive personality. Two case histories illustrate some of the complexities of assessing impairment in workers with personality disorders, including drug abuse, hospitalizations, and inpatient and outpatient psychotherapy.


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