Collaborative annotation for context-aware retrieval

Mizzaro, Stefano; Nazzi, Elena; Vassena, Luca

doi:10.1145/1506250.1506260

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…Moreover, a folksonomy-based approach to context modeling can aggregate not only real data and metadata from devices at home but even user-provided information about his context. Similar approach has been considered in (Mizzaro et al, 2009) …”

Section: Context Modelingmentioning

confidence: 97%

An AmI-Enabled OSGi Platform Based on Socio-Semantic Technologies

Vilas¹,

Redondo²,

Pazos‐Arias³

et al. 2010

Smart Home Systems

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Ideally, smart homes should make its inhabitants' lives more comfortable by anticipating their needs and satisfying their preferences. With this aim, we introduce an approach for contextaware personalized smart homes based on three pillars: the Open Service Gateway Initiative (OSGi) platform, the Semantic Web philosophy and the collaborative tagging trends. By combining these fields, we enrich the OSGi service-oriented architecture by providing a semantical conceptualization of services at home. On the top of this semantic formalization of services, we support context-awareness personalization by using a dynamic and non previously agreed structure for modeling context: a folksonomy. This socio-semantic approach to the problem takes into account the heterogeneous nature of the devices which provide contextual information so that defining a previously agreed constrained vocabulary for context is unrealistic.

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Section: Context Modelingmentioning

confidence: 97%

An AmI-Enabled OSGi Platform Based on Socio-Semantic Technologies

Vilas¹,

Redondo²,

Pazos‐Arias³

et al. 2010

Smart Home Systems

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show abstract

“…Each tag is banally a keyword or string of text and represents a single contextual value [8]. We divide the contextual tags into two categories:…”

Section: Context Representationmentioning

confidence: 99%

A social approach to context-aware retrieval

Mizzaro

Vassena

2011

World Wide Web

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In this paper we present a general purpose solution to Web content perusal by means of mobile devices, named Social Context-Aware Browser. This is a novel approach for the information access based on the users' context, whose aim is to retrieve what the user needs, even if she did not issue any query. Our solution is built upon a social model that exploits the collaborative efforts of the whole community of users to control and manage contextual knowledge, related both to situations and resources. This paper presents a general survey of our solution, describing the idea and presenting an implementation approach.

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“…The similar preferences or properties are the basis of collaborative acquisition or recommendation. In the process of social tagging, different users will annotate the same resource with the same tags based on their similar preferences; different resources will be tagged with the same tags by the same user based on their similar properties (Mizzaro et al , 2009). In the application of collaborative acquisition or recommendation, the recognition of similar preferences helps in acquiring or recommending the same resources to different users who have similar preferences; the recognition of similar properties also helps in acquiring or recommending different resources that have similar properties to the same user.…”

Section: Annotation and Association Of Social Taggingmentioning

confidence: 99%

Personalisation and sociability of open knowledge management based on social tagging

Lee

2010

Online Information Review

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PurposeThe purpose of this paper is to analyse the personalised and social characteristics of open knowledge management in higher education based on social tagging in the Web 2.0 environment.Design/methodology/approachThrough the function of annotation in social tagging, the paper analyses its personalised characteristics of recognising the preferences of participants, and its personalised‐social characteristics of enriching content from all kinds of aspects; through the function of association of social tagging, it analyses its social characteristics of social networking, and its social‐personalised characteristics of collaborative acquisition or recommendation.FindingsIn the process of online information and open knowledge organisation and acquisition based on the annotation function of social tagging in the Web 2.0 environment, the personalised participation of individuals will lead to social results for everyone; however, in the process of online information and open knowledge creation and sharing based on the association function of social tagging, social and collaborative sharing among participants will help with personalised knowledge allocation.Originality/valueIn open knowledge management in higher education, the characteristics of personalisation and sociability based on social tagging will help to personalise the organisation and acquisition of knowledge, and help with social creation and sharing of knowledge.

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Collaborative annotation for context-aware retrieval

Cited by 7 publications

References 6 publications

An AmI-Enabled OSGi Platform Based on Socio-Semantic Technologies

An AmI-Enabled OSGi Platform Based on Socio-Semantic Technologies

A social approach to context-aware retrieval

Personalisation and sociability of open knowledge management based on social tagging

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