Survey on Mobile Optimized Search Crawler
Survey Paper | Journal Paper
Vol.3 , Issue.10 , pp.99-102, Oct-2015
Abstract
The web crawler is the central component of a search engine which works like an indexer, finds out hyperlinks and computes keyword density of each web page. It assigns a page rank to each crawled web page by using some ranking algorithm and stores the visited links for the future use. Search results retrieve very fast from desktop browser, but it takes more time when user is on mobile. When a keyword is searched from a mobile browser, the traditional web servers take a long time to interpret this request. Also, the web server has to format search results into the form which mobile device can interpret. Thus, to eliminate this overhead on the web server, a Mobile Application Server has to be introduced instead of the web server to interpret requests from mobile devices.
Key-Words / Index Term
Search engine; Crawler; Web server; Mobile application server; Wireless markup language; Wireless application protocol
References
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[11] “Mobile Application Server”,
http://www.mobileinfo.com/application_servers.htm ,
4 July, 2015.
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Citation
Kukreja Kajal, Gavali Nishigandha and Khedlekar Gandhali, "Survey on Mobile Optimized Search Crawler," International Journal of Computer Sciences and Engineering, Vol.3, Issue.10, pp.99-102, 2015.
Supervised Random Walks for Predicting Links in Social Networks: A Study
Review Paper | Journal Paper
Vol.3 , Issue.10 , pp.103-105, Oct-2015
Abstract
Predicting is future relationships from a given snapshot of a network or to infer the interactions among existing members that are likely to occur in the near future is called as link prediction. One of the interesting areas of research in social network is prediction of links. There are various techniques for inferring missing links or additional links that are not directly visible but may occur in the future. Random walk is a popular approach which uses node and edge features to solve the problem of link prediction. Supervised random walks combine the network structure with the characteristics of nodes and edges and acts as a powerful tool for predicting the missing and future links. In this paper a study has been made on various algorithms that uses supervised random walk approach for predicting links in social networks.
Key-Words / Index Term
Social networks, Link prediction, Supervised Random walk
References
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[11] Zhijun yin,Manish Gupta, Tim Weninger and Jiawei Han, A Unified Framework for Link Recommendation Using Random Walks, Advances in Social Networks Analysis and Mining (ASONAM), 2010 International Conference, 2010,pp.152 – 159.
Citation
A.Vihashini and G.T.Prabavathi, "Supervised Random Walks for Predicting Links in Social Networks: A Study," International Journal of Computer Sciences and Engineering, Vol.3, Issue.10, pp.103-105, 2015.