Towards a Tag-Based User Model: How Can User Model Benefit from Tags?

Carmagnola, Francesca; Cena, Federica; Cortassa, Omar; Gena, Cristina; Torre, Ilaria

doi:10.1007/978-3-540-73078-1_62

Cited by 55 publications

(40 citation statements)

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“…Traditional user modeling methods are divided into explicit user modeling and implicit user modeling according to user access to information, the former gets user interests and preferences directly, and the latter does this by inference [1]. The user model is constructed using a variety of techniques including neural network [2,3], keyword statistics [4,5], ontology [6][7][8], tag [9] and social network [10][11][12]. Ontology expresses complex conceptual relations and provides a common framework that allows information to be shared and reused, ontologybased user modeling is the use of ontology to structure user model, so it reflects the actual user needs, and we focus on the role of semantically enhanced user modeling for personalized recommendation service.…”

Section: Introductionmentioning

confidence: 99%

Ontology-based User Modeling for Chinese Crop Germplasm Resources Information System

Chen¹,

Si²,

Fang³

et al. 2017

IJHIT

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Section: Introductionmentioning

confidence: 99%

Ontology-based User Modeling for Chinese Crop Germplasm Resources Information System

Chen¹,

Si²,

Fang³

et al. 2017

IJHIT

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“…Other than these original functions, the data prove to be highly valuable in many other fields. For example, annotations can help enhance Web search [6,35], generate user profiles [23], personalize recommendations and other user experiences [7,29], improve social navigation and information accessibility [16,3,15], promote semantic Web techniques and construction of ontologies [13]. However, users share annotations largely for individual needs and aspirations, sometimes leading to low-quality annotation data.…”

Section: Introductionmentioning

confidence: 99%

Emergent semantics from game-induced folksonomies

Weng

Menczer

2012

Proceedings of the First International Workshop on Crowdsourcing and Data Mining

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We describe the GiveALink Slider, an experimental social tagging game designed with the purpose of generating meaningful and useful annotations to improve upon the drawbacks of existing folksonomies. Knowledge, in the form of reliable annotations, is validated and accumulated through the implicit interactions among multiple players. In this paper we explore the hypothesis that such a game can improve both the quality and quantity of social annotation data. Our evaluation of game-induced annotations shows that games may improve on the semantic structure of existing folksonomies from several perspectives, including searchability, novelty, and coherence. Games can therefore play a valuable role in the collection of helpful annotations, by leveraging human power and specific game design features.

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“…However, it is interesting to investigate the meaning the tags may assume in relation to their specific context of use. This is the reason why our classification takes into account the experiment of Carmagnola et al (2007), described in detail in Section 5. This work has identified a number of categories of tags related to their usage (Proposed Tags, Free Tags, General tags, Specific Tags, Synonym Tags, Contextual tags, and Subjective Tags).…”

Section: Analyzing the Meaning Of Tagsmentioning

confidence: 99%

“…Tags can be useful in increasing and optimizing the system knowledge about users (Carmagnola et al, 2007). In order to consider this enhanced user model in PAPERE, we propose to analyze social annotations, and primarily, the tagging activity from a quantitative and a qualitative point of view.…”

Section: A Web 20 Enhanced User Modelmentioning

confidence: 99%

Tag-based user modeling for social multi-device adaptive guides

Carmagnola

Cena

Console

et al. 2008

User Model User-Adap Inter

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Abstract.This paper aims to demonstrate that the principles of adaptation and user modeling, especially social annotation, can be integrated fruitfully with those of the Web 2.0 paradigm and thereby enhance in the domain of cultural heritage. We propose a framework for improving recommender systems through exploiting the users tagging activity. We maintain that Web 2.0's participative features can be exploited by adaptive web-based systems in order to enrich and extend the user model, improve social navigation and enrich information from a bottom-up perspective. Thus our approach stresses social annotation as a new and powerful kind of feedback and as a way to infer knowledge about users. The prototype implementation of our framework in the domain of cultural heritage is named iCITY. It is serving to demonstrate the validity of our approach and to highlight the benefits of this approach specifically for cultural heritage. iCITY is an adaptive, social, multi-device recommender guide that provides information about the cultural resources and events promoting the cultural heritage in the city of Torino. Our paper first describes this system and then discusses the results of a set of evaluations that were carried out at different stages of the systems development and aimed at validating the framework and implementation of this specific prototype. In particular, we carried out a heuristic evaluation and two sets of usability tests, aimed at checking the usability of the user interface, specifically of the adaptive behavior of the system. Moreover, we conducted evaluations aimed at investigating the role of tags in the definition of the user model and the impact of tags on the accuracy of recommendations. Our results are encouraging.

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Towards a Tag-Based User Model: How Can User Model Benefit from Tags?

Cited by 55 publications

References 0 publications

Ontology-based User Modeling for Chinese Crop Germplasm Resources Information System

Ontology-based User Modeling for Chinese Crop Germplasm Resources Information System

Emergent semantics from game-induced folksonomies

Tag-based user modeling for social multi-device adaptive guides

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