A Logical Inference Approach to Query Expansion with Social Tags

Lioma, Christina; Blanco, Roi; Moens, Marie‐Francine

doi:10.1007/978-3-642-04417-5_39

Cited by 5 publications

(3 citation statements)

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“…Lioma et al [19] provide Social QE by considering query expansion as a logical inference and by considering the addition of tags as an extra deduction to this process. In the same spirit, Jin et al [20] propose a method in which the used expansion terms are selected from a large amount of social tags in folksonomy.…”

Section: Non-personalized Social Query Expansionmentioning

confidence: 99%

“…Examples of such systems include Yahoo Answer!, 15 WikiAnswers, 16 Aardvark, 17 Chacha, 18 and Ask.com. 19 Basically, Q&A systems provide a means for answering several types of questions such as recommendation, e.g., building a new play list, any ideas for good running songs?, opinion seeking, e.g., I am wandering if I should buy the Kitchen-Aid ice cream maker?, factual knowledge, e.g., Does anyone know a way to put Excel charts into LaTeX? problem solving, e.g., How do I solve this Poisson distribution problem?…”

Section: Social Question/answering (Qanda)mentioning

confidence: 99%

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Social networks and information retrieval, how are they converging? A survey, a taxonomy and an analysis of social information retrieval approaches and platforms

Bouadjenek

Hacid

Bouzeghoub

2016

Information Systems

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a b s t r a c tThere is currently a number of research work performed in the area of bridging the gap between Information Retrieval (IR) and Online Social Networks (OSN). This is mainly done by enhancing the IR process with information coming from social networks, a process called Social Information Retrieval (SIR). The main question one might ask is What would be the benefits of using social information (no matter whether it is content or structure) into the information retrieval process and how is this currently done?With the growing number of efforts towards the combination of IR and social networks, it is necessary to build a clearer picture of the domain and synthesize the efforts in a structured and meaningful way. This paper reviews different efforts in this domain. It intends to provide a clear understanding of the issues as well as a clear structure of the contributions. More precisely, we propose (i) to review some of the most important contributions in this domain to understand the principles of SIR, (ii) a taxonomy to categorize these contributions, and finally, (iii) an analysis of some of these contributions and tools with respect to several criteria, which we believe are crucial to design an effective SIR approach. This paper is expected to serve researchers and practitioners as a reference to help them structuring the domain, position themselves and, ultimately, help them to propose new contributions or improve existing ones.

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Section: Non-personalized Social Query Expansionmentioning

confidence: 99%

Section: Social Question/answering (Qanda)mentioning

confidence: 99%

Social networks and information retrieval, how are they converging? A survey, a taxonomy and an analysis of social information retrieval approaches and platforms

Bouadjenek

Hacid

Bouzeghoub

2016

Information Systems

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“…Zha, 2002). Let me give two examples: In the broader field of IR, Lioma, Blanco, and Moens (2009) use salience as a means of query expansion. In this case social tags are used to expand user queries.…”

Section: In the Information Science Community Automatic Summarizationmentioning

confidence: 99%

Empirically measuring salience of objects for use in pedestrian navigation

Kattenbeck

2015

Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

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Auch wenn sie es vehement von sich weisen würden, so haben meine Eltern großen Anteil an dieser, meiner Dissertation. Sie gaben mir von Kindesbeinen an die Freiheit, mich mit dem Nachdenken auseinanderzusetzen. Glaubt mir, Mama und Papa, ohne diese Freiheit wäre ich heute nicht der, der ich bin.Schließlich danke ich meiner über alles geliebten Frau Anita. Wir sind fast genau so lange verheiratet, wie es gedauert hat, bis ich nun mein Promotionsverfahren erfolgreich abschließen konnte. In diesen Jahren haben wir einiges zusammen erlebt und durchgemacht.Du, Anita, hast immer zu mir gehalten und mich in Allem und mit Allem unterstützt.Ohne Dich, Anita, wäre diese Arbeit undenkbar.Dir, Anita, widme ich diese Arbeit.vi A B S T R A C T background Humans usually refer to landmarks when they give route directions to pedestrians. One of the reasons why current mobile pedestrian navigation systems do not yet mimic this mode of communication is the lack of available data sources. The usefulness of a crowd-sourced data acquisition approach to overcome this problem has long been mooted. However, to date no empirically sound way of measuring the salience of objects by means of surveys exists.goal Given this background, this doctoral work has three goals:1. To achieve a sound way of measuring salience and its subdimensions, i.e. visibility in advance, cognitive salience, prototypicality, structural salience, and visual salience based on taking dimensions revealed in earlier studies systematically and simultaneously into account.2. To find subgroups of visual features among the large number of visual attributes known from the literature.3. To find the most important subdimensions of salience by means of estimating two different structural equation models. Model I is based on assumptions of independence among subdimensions, whereas model II reflects hypotheses of mediation.Taken as a whole, achieving these goals will foster both, the advancement of theories of salience and landmark acquisition methods.methodology A large scale, in-situ experiment was implemented, trying to overcome weaknesses of earlier attempts made to estimate salience. An vii appropriate sample size of buildings and non-buildings was calculated a priori (n obj = 360). Objects were randomly selected based on their geographical coordinates and randomly grouped into n r = 55 routes. Participants were required to rate objects by means of a survey. The questions were derived from empirical evidence found in earlier studies. Each route was walked by two different participants (n = 112), id est (i.e.) two ratings per object were collected for data analysis.findings Model I and model II were analyzed using PLS Path Modeling and consistent PLS Path Modeling, respectively. The measurement models proposed showed a good fit, although some weaknesses were identified for prototypicality and cognitive salience. Geometrical aspects as well as features like (visual) age turned out to have a stronger impact on visual salience than color. Model I did not yield reasonable struct...

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