Retrieval of context-aware applications on mobile devices

Mizzaro, Stefano; Nazzi, Elena; Vassena, Luca

doi:10.1145/1414694.1414710

Cited by 17 publications

(11 citation statements)

References 9 publications

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“…The test collection approach for Mobile IR has been proposed by Mizzaro et al [133], and used in a number of papers by the same group [46,128,129,132] to evaluate various context-aware retrieval prototypes MoBe, CAB, and SCAB that they developed (see Section 7.2.3 for detailed descriptions). There are mainly three attempts to evaluation, corresponding to the three different prototypes.…”

Section: Early Attemptsmentioning

confidence: 99%

From IR to Mobile IR

Crestani

Mizzaro

Scagnetto

2017

Mobile Information Retrieval

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https://adwords.googleblog.com/2015/05/building-for-next-moment. html * The use of the word "mainly" here indicates that the boundary between the two areas is becoming fuzzy, with some IR systems working in a more deterministic way and DB systems working in a more probabilistic or "uncertainty conscious" fashion. * The semantic meaning of different words is inferred using a deep learning technique named word2vec, https://code.google.com/p/word2vec/.† https://code.google.com/p/androguard/ * trec.nist.gov † research.nii.ac.jp/ntcir/index-en.html ‡ https://sites.google.com/site/treccontext/

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Section: Early Attemptsmentioning

confidence: 99%

From IR to Mobile IR

Crestani

Mizzaro

Scagnetto

2017

Mobile Information Retrieval

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“…A more general system is represented by the MoBe framework [7]. In this application, a general inferential framework (based on ontologies and Bayesian networks) combines the information coming from sensors to infer new and more abstract contexts (user activities, needs, etc.…”

Section: Context-aware Retrievalmentioning

confidence: 99%

“…This approach is named Social Context-Aware Browser and its novelty is threefold. First of all this is a new radical approach that aims at discovering "the query behind the context": to retrieve what the user needs, even if she did not issue any query [7]. Second this is not a domain dependent application, but a new generic way of interaction and information access, able to adapt to every domain.…”

Section: Introductionmentioning

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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“…We submit the total queries to yahoo boss search API 3 , and crawled the top 50 obtained results for each query. These documents are presented for relevance judgment to our diary study participants via an assessment tool available on line and developed in our lab 4 . The user interests are integrated in the evaluation protocol according to an automatic algorithm that generates them based on the users manual judgments of the documents like described in section 3.1.…”

Section: Evaluation Framework Applicationmentioning

confidence: 99%

“…In [4], authors propose a contextual simulation framework based on a set of simulated context descriptors that include location, time and user activities. User's queries are automatically formulated from the context descriptors using different techniques.…”

Section: Introductionmentioning

confidence: 99%

A Diary Study-Based Evaluation Framework for Mobile Information Retrieval

Bouidghaghen¹,

Tamine²

2010

Information Retrieval Technology

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In this poster, we propose an evaluation framework that investigates the integration of the user context (interests, location and time) into the evaluation process of mobile IR. Our approach is based on a diary study where users are asked to log their queries annotated by their location and time. Users' interests are explicitly acquired or implicitly learned based on users' relevance judgments for the retrieved documents answering their queries. We propose two evaluation protocols namely training/test in chronological order and k-fold cross validation. We exploit this framework in order to evaluate the performance of our context-based personalized mobile search approach. Experimental results show the stability performance of our approach according to the proposed evaluation protocols and demonstrate the viability of the diary approach as a means to capture context in evaluation.

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Retrieval of context-aware applications on mobile devices

Cited by 17 publications

References 9 publications

From IR to Mobile IR

From IR to Mobile IR

A social approach to context-aware retrieval

A Diary Study-Based Evaluation Framework for Mobile Information Retrieval

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