Now a days, there is huge growth in the use of mobile devices. As apps are comes from various vendors may have similar functionality. Hence, user may confused that which app is better to use for time efficiently manner. Hence, App classification works better for classification app according to their functionality. Mobile devices have limited contextual information such as, app name and its label which is not sufficient for identifying proper functionality of particular app. Different methods are used to classify app that uses sparse and short information. Here an app classification system, to make easy to understand user’s preferences. This system may works on three levels known as, dealing with related collection of an app, second is to manage this collected information, and third are form categories of this information for making decision of whether to use particular app or not. As a part of our contribution we recommend app list to user end based on his profile. Therefore, in this paper mainly carried out app classification as well as app recommendation.
Ashwini Sanap, M. B. Vaidya
Mobile App Classification,Web Knowledge, Information Contexts, Smart Phone Apps.
- Hengshu Zhu, Enhong Chen, Senior Member, IEEE, Hui Xiong, Senior Member,IEEE,Huanhuan Cao, and Jilei Tian "Mobile App Classification with Enriched Contextual Information",IEEE Trans. on Mobile Computing JULY 2014
- Kahng, S. Lee, and S.-G. Lee, "Ranking in context-aware recom-mender systems" , in Proc. WWW, Hyderabad, India, 2011, pp. 6566.
- Li, H. Cao, H. Xiong, E. Chen, and J. Tian,"BP-growth:Searching strategies for efficient behavior pattern mining", in Proc. MDM, Bengaluru, India, 2012, pp. 238247.
- Malouf," A comparison of algorithms for maximum entropy parameter estimation," in Proc. COLING,Stroudsburg, PA, USA, 2002, pp.17.
- Nigam, "Using maximum entropy for text classification", in Proc. IJCAI Workshop Machine Learning for Information Filtering, 1999, pp. 6167.f. Image Process., Nov. 2009,pp. 8992.
- -H. Phan et al., "A hidden topic-based framework toward building applications with short web documents", IEEE Trans. Knowl. Data Eng, Jul. 2010.
- Sahami and T. D. Heilman, "A web-based kernel function for mea- suring the similarity of short text snippets", in Proc. WWW, Edin- burgh, U.K., 2006, pp. 377386.
- Shen, J.-T. Sun, Q. Yang, and Z. Chen,"Building bridges for web query classification", in Proc. SIGIR, Seattle, WA, USA, 2006, pp. 131138.
- Zhu, H. Cao, E. Chen, H. Xiong, and J. Tian, "Exploiting enriched contextual information for mobile app classification", in Proc. CIKM, Maui, HI, USA, 2012, pp. 16171621.
- Zhu, H. Cao, H. Xiong, E. Chen, and J. Tian," Towards expert finding by leveraging relevant categories in authority ranking", in Proc. CIKM, Glasgow, U.K., 2011, pp. 22212224.
- Zhu et al., "Mining personal context-aware preferences for mobile users", in Proc. ICDM, Brussels, Belgium, 2012, pp. 12121217.
- Cao et al., "Context-aware query classification", in Proc. SIGIR, Boston, MA, USA, 2009, pp. 310.
- Z. Broder et al., "Robust classification of rare queries using web knowledge", in Proc. SIGIR, Amsterdam, Netherlands, 2007, pp. 231238.
- Bao, H. Cao, E. Chen, J. Tian, and H. Xiong, "An unsupervised approach to modeling personalized contexts of mobile users", in Proc. ICDM, Sydney, NSW, Australia, 2010, pp. 3847.
- L. Berger, V. J. D. Pietra, and S. A. D. Pietra, "A maximum entropy approach to natural language processing, Comput.Linguist"., vol. 22, no. 1, pp. 3971, Mar. 1996.
|Published in :
||Volume 2 | Issue 5 | September-October - 2016
|Date of Publication
Cite This Article
Ashwini Sanap, M. B. Vaidya, "By Analyzing the App Reviews Profile Based Mobile App Recommendation Using Contextual Information of App", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 5, pp.163-166, September-October-2016.
URL : http://ijsrset.com/IJSRSET162542.php