Web site clustering consists in finding meaningful groups of related web sites. How related is some web site to an-other is a question that depends on how we represent websites. Traditionally, vectors and graphs have been two important structures to represent individuals in a population.Both representations can play an important role in the web area if hyper structure is considered. By analyzing the way web sites are linked, we can build vectors or graphs to understand how a web site collection is partitioned.99 Android Projects Ideas Titles 2019 2020 In this paper, we analyze these two models and four associated algorithms: k-means and self-organizing maps (SOM) with vectors, simulated annealing and genetic algorithms with graphs.
For testing these ideas we clustered some web sites in the Central American web. We compare the results for clustering this web site collection using both models and show what kind of clusters each one produces.
The World Wide Web(WWW) is the most extended, flexible and heterogeneous library of our time Virtually,every topic can be found in this huge collection of documents. Part of the WWW’s success is due to the easy way in which documents can be added to this library. There is neither global referee nor established themes nor language restrictions for contribute to the web. However, this same feature makes WWW a collection very difficult to analyze.So much flexibility has its price.Web Mining is an area of study that tries to over come this barrier by analyzing the properties of the web and finding patterns that help programs to satisfy the information need of a user.99 Android Projects Ideas Titles 2019 2020 Many of these patterns are introduced into web crawlers to provide a good way to find high quality in-formation, given a query. By examining the structure and composition of web pages and web sites, many properties can be obtained. Also, the web clustering problem can also be addressed. This problem states the question of how web objects are grouped. Whether web documents or web sites are treated depend on the granularity of the problem. Typically, web documents are clustered and this result can be applied into several tasks: web document indexing, web document ranking, web browsing, and the like.Nevertheless, web site clustering is also an important problem, given that web communities can be discovered.
The resultant groups can be understood as closely related web sites according to the presented information. Again,this grouping can be done using the content of each website as well as the structure of the web site collection.This paper presents two forms to represent web sites for clustering when the structure generated by the links among web sites is considered. It is divided into the following sections.99 Android Projects Ideas Titles 2019 2020 The first revisits the related work.presents the first model, where web sites are represented with points in a vectorial space.offers a tour for the graph model, where web site clusters are represented by components in graph theory. Then, Section presents the experiments done and the results obtained when comparing the models with the test case (Central American web sites).Finally, conclusions and future work are left for Section
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