Searching Steiner trees for web graph query

The enormous growth in information technology has revolutionized the way people can access information sources. Web search engines have played an important role to support what the user wants precisely and efficiently from the vast web database. Different from conventional search engine approaches, searching the structure of the web, where the answer comprises more than a single page connected by hyperlinks, needs to be meritoriously developed. We propose Linear Programming models in order to generate the optimal structured web objects searching for relevant web graphs. In the model, the web objects with node and edge weights that represent the ranking measures for Webpages and hyperlinks are devised to rank the relevance in terms of keyword vectors. We also developed a tree-filtering algorithm and top-k Steiner tree algorithm that is used to provide the search recommendations in practical applications. With real web databases, the experimental study shows that the LP approach outperforms the conventional search engines with respect to execution time and quality of results.