Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-32320-1_12
DC FieldValue
dc.titleMobilewalla: A mobile application search engine
dc.contributor.authorDatta, A.
dc.contributor.authorDutta, K.
dc.contributor.authorKajanan, S.
dc.contributor.authorPervin, N.
dc.date.accessioned2013-07-11T10:17:47Z
dc.date.available2013-07-11T10:17:47Z
dc.date.issued2012
dc.identifier.citationDatta, A.,Dutta, K.,Kajanan, S.,Pervin, N. (2012). Mobilewalla: A mobile application search engine. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 95 LNICST : 172-187. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-32320-1_12" target="_blank">https://doi.org/10.1007/978-3-642-32320-1_12</a>
dc.identifier.isbn9783642323195
dc.identifier.issn18678211
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/42776
dc.description.abstractWith the popularity of mobile apps on mobile devices based on iOS, Android, Blackberry and Windows Phone operating systems, the number of mobile apps in each of the respective native app stores are increasing in leaps and bounds. Currently there are almost 700,000 mobile apps across these four major native app stores. Due to such enormous number of apps, both the constituents in the app ecosytem, consumers and app developers, face problems in terms of 'app discovery'. For consumers, it is a daunting task to discover the apps they like and need among the huge number of available apps. Likewise, for developers, making it possible for users to discover their apps in the large number of available apps is a challenge. To address these issues, Mobilewalla(MW), provides an independent unbiased search engine for mobile apps with semantic search capabilities. It has also developed an objective scoring mechanism based on user and developer involvement with an app. The scoring mechanism enables MW to provide a number of other ways to discover apps - such as dynamically maintained 'hot' lists and 'fast rising' lists. In this paper, we describe the challenges of developing the MW platform and how these challenges have been mitigated. Lastly, we demonstrate some of the key functionalities of MW. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-32320-1_12
dc.sourceScopus
dc.subjectMobile App
dc.subjectSearch Engine
dc.subjectSemantic Similarity
dc.typeConference Paper
dc.contributor.departmentINFORMATION SYSTEMS
dc.description.doi10.1007/978-3-642-32320-1_12
dc.description.sourcetitleLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
dc.description.volume95 LNICST
dc.description.page172-187
dc.identifier.isiutNOT_IN_WOS
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