With the increase in number of pages being published every day, there is a need to design an efficient crawler mechanism which can result in appropriate and efficient search results for every query. Everyday people face the problem of inappropriate or incorrect answer among search results. So, there is strong need of enhance methods to provide precise search results for the user in acceptable time frame. So this paper proposes an effective approach of building a crawler considering factors of URL ranking, load on the network and number of pages retrieved. The main focus of the paper is on designing of a crawler to improve the effective ranking of URLs using a focused crawler.
In a large collection of web pages, it is difficult for search engines to keep their online repository updated. Major search engines have hundreds of web crawlers that crawl the WWW day and night and send the downloaded web pages via a network to be stored in the search engine’s database. These results in over utilization of network resources like bandwidth, CPU cycles and so on. This paper proposes an architecture that tries to reduce the utilization of shared network resources with the help of an advanced XML based approach. This focused crawling based architecture is trained to download only the high quality data from the internet leaving behind the web pages which are not relevant to the desired domain. Here, a detailed layout of the proposed system is described which is capable of reducing the load on network and reducing the problem arise in residency of mobile agent at the remote server.
Semantic query optimization is applied to relational databases using the inductive learning approach. This approach generates an alternate query using the learning framework and the algorithm. The alternate query should be semantically equivalent to original query. The semantically equivalent query generated should be less expensive than the original query. These can be implemented in SQL using the SQL hints. These hints allow user to implement the desired plan for the query.
Query optimization in databases has gain a lot of importance in recent years. In this paper, we have analyzed different techniques of query optimization in relational databases and compared their performance. We have covered the techniques which use different methods for query representation.
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