Abstract—Traditional text search engines accomplish document retrieval by taking a query from the user, and then returning a set of documents matching the user’s query. A web search engine often returns thousands of pages in response to a broad query. This makes it very difficult for users to browse or to identify relevant information from the results returned. In order to retrieve the documents of interest, the user must formulate the query using the keywords that appear in the documents. This is a difficult task, if not impossible, for ordinary people who are not familiar with the vocabulary of the data corpus. Clustering methods can be used to automatically group the retrieved documents into a sorted list of meaningful categories by analyzing the results for related content.
Index Terms—Search engine, PageRank, Automatic Link Generation, Web-site clustering.
Reyner D’souza and Apurva Kulkarni are with Don Bosco Institute of Technology, Mumbai, India (e-mail: rynrdsouza@gmail.com).
Imran Ali Mirza is with the Department of Computer Engineering, Don Bosco Institute of Technology, Mumbai, India.
Cite: Reyner D’souza, Apurva Kulkarni, and Imran Ali Mirza, "Automatic Link Generation for Search Engine Optimization," International Journal of Information and Education Technology vol. 2, no. 4, pp. 401-403, 2012.