A Hybrid Architecture for User-Adapted Information Filtering on the World Wide Web

Ambrosini, Leonardo; Cirillo, Vincenzo; Micarelli, Alessandro

doi:10.1007/978-3-7091-2670-7_8

Cited by 18 publications

(9 citation statements)

References 4 publications

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“…Besides explicit triggers, other mechanisms may be used for stereotype activation, like neural networks (Ambrosini et al, 1997). A further development of stereotype reasoning was led by the idea that one can also group the required preconditions for the activation of stereotypes into disjoint categories, thus arriving at more general stereotype models.…”

Section: Stereotype Reasoningmentioning

confidence: 99%

“…The stereotype approach has been used in many systems (Ambrosini et al, 1997;Fink et al, 1998;Kobsa et al, 1994;Moore & Paris, 1992, to name but a few). The importance of the stereotype approach is reflected by the fact that stereotyping is one of the few common features of the so-called "user modelling shell systems" that were built in the mid-1990s as toolboxes for the development of user modelling systems.…”

Section: Stereotype Reasoningmentioning

confidence: 99%

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Personalised hypermedia presentation techniques for improving online customer relationships

Kobsa

Koenemann²,

Pohl

2001

The Knowledge Engineering Review

407

298

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This article gives a comprehensive overview of techniques for personalised hypermedia presentation. It describes the data about the computer user, the computer usage and the physical environment that can be taken into account when adapting hypermedia pages to the needs of the current user. Methods for acquiring these data, for representing them as models in formal systems and for making generalisations and predictions about the user based thereon are discussed. Different types of hypermedia adaptation to the individual user's needs are distinguished and recommendations for further research and applications given. While the focus of the article is on hypermedia adaptation for improving customer relationship management utilising the World Wide Web, many of the techniques and distinctions also apply to other types of personalised hypermedia applications within and outside the World Wide Web, like adaptive educational systems.

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Section: Stereotype Reasoningmentioning

confidence: 99%

Section: Stereotype Reasoningmentioning

confidence: 99%

Personalised hypermedia presentation techniques for improving online customer relationships

Kobsa

Koenemann²,

Pohl

2001

The Knowledge Engineering Review

407

298

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“…The filtering component in HUMOS-Hybrid User Modeling Subsystem (Ambrosini, Cirillo, & Micarelli, 1997) is based on stereotypes. A case-based approach is proposed for the task of automatically inferring user stereotypes.…”

Section: Information Filtering Based On Stereotypesmentioning

confidence: 99%

Stereotype‐based versus personal‐based filtering rules in information filtering systems

Kuflik

Shapira

Shoval

2003

J. Am. Soc. Inf. Sci.

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Rule-based information filtering systems maintain user profiles where the profile consists of a set of filtering rules expressing the user's information filtering policy. Filtering rules may refer to various attributes of the data items subject to the filtering process. In personal rulebased filtering systems, each user has his/her own personal filtering rules. In stereotype rule-based filtering systems, a user is assigned to a group of similar users (his/her stereotype) from which he/she inherits the stereotype's filtering profile. This study compares the effectiveness of the two alternative rule-based filtering methods: stereotype-based rules versus personal rules. We conducted a comparison between filtering effectiveness when using the personal rules or when using the stereotype-based rules. Although, intuitively, personal filtering rules seem to be more effective because each user has his own tailored rules, our comparative study reveals that stereotype filtering rules yield more effective results. We believe that this is because users find it difficult to evaluate their filtering preferences accurately. The results imply that by using a stereotype it is possible not only to overcome the problem of user effort required to generate a manual rule-based profile, but at the same time even provide a better initial user profile.

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“…A user model is a knowledge source which contains explicit assumptions on all aspects of the user that are relevant to the interactive behaviour of the software application. User modeling technology has also been integrated into information filtering systems (Ambrosini et al, 1997).…”

Section: New Technologies In Education and Training Contextsmentioning

confidence: 99%

The role of the library in a new learning scenario

Bargellini¹,

Bordoni²

2001

The Electronic Library

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.

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A Hybrid Architecture for User-Adapted Information Filtering on the World Wide Web

Cited by 18 publications

References 4 publications

Personalised hypermedia presentation techniques for improving online customer relationships

Personalised hypermedia presentation techniques for improving online customer relationships

Stereotype‐based versus personal‐based filtering rules in information filtering systems

The role of the library in a new learning scenario

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