WebTrovert: An AutoSuggest Search and Suggestions Implementing Recommendation System Algorithms
There are hundreds of websites and apps that are struggling to find the algorithms for the perfect search to optimize the website’s resources, however we have very few success stories.
We aim to build in this paper, a recommendation system, WebTrovert, which is based on practically designed algorithms. It comprises of a social networking platform holding user information and their data in the form of documents and videos.
It incorporates autosuggest search and suggestions to enhance the productivity and user friendliness of the website.
Unable to display preview. Download preview PDF.
- 1.Agarwal, A., Annapoorani, L., Tayal, R., Gujral, M.: Recommendation systems : A practical approach (Yet To Be Published)Google Scholar
- 2.Gipp, B., Beel, J., Hentschel, C.: Scienstein: A Research Paper Recommender System. In: Proceedings of the International Conference on Emerging Trends in Computing (ICETiC 2009), pp. 309–315 (2009)Google Scholar
- 3.Garcia-Molina, H., Koutrika, G., Parameswaran, A.: Information Seeking: Convergence of Search, Recommendations and Advertising. ACM Transactions on Information Systems, Stanford UniversityGoogle Scholar
- 4.Linden, G., Smith, B., York, J.: Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing (January 2003)Google Scholar
- 5.Rashotte, L.: Social influence. In: Ritzer, G. (ed.) Blackwell Encyclopedia of Sociology, pp. 4426–4429 (2007)Google Scholar
- 6.Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: An open architecture for collaborative filtering of Netnews. In: Proc. ACM Conference on Computer Supported Cooperative Work. ACM Press, Chapel Hill, North Carolina, United States(1994)Google Scholar