The information access is the rich data available for information retrieval, evolved to provide principle approaches or strategies for searching. For building the successful web retrieval search engine model, there ar...The information access is the rich data available for information retrieval, evolved to provide principle approaches or strategies for searching. For building the successful web retrieval search engine model, there are a number of prospects that arise at the different levels where techniques, such as Usenet, support vector machine are employed to have a significant impact. The present investigations explore the number of problems identified its level and related to finding information on web. The authors have attempted to examine the issues and prospects by applying different methods such as web graph analysis, the retrieval and analysis of newsgroup postings and statistical methods for inferring meaning in text. The proposed model thus assists the users in finding the existing formation of data they need. The study proposes three heuristics model to characterize the balancing between query and feedback information, so that adaptive relevance feedback. The authors have made an attempt to discuss the parameter factors that are responsible for the efficient searching. The important parameters can be taken care of for the future extension or development of search engines.展开更多
An improved decision tree method for web information retrieval with self-mapping attributes is proposed.The self-mapping tree has a value of self-mapping attribute in its internal node,and information based on dissimi...An improved decision tree method for web information retrieval with self-mapping attributes is proposed.The self-mapping tree has a value of self-mapping attribute in its internal node,and information based on dissimilarity between a pair of mapping sequences.This method selects self-mapping which exists between data by exhaustive search based on relation and attribute information.Experimental results confirm that the improved method constructs comprehensive and accurate decision tree.Moreover,an example shows that the self-mapping decision tree is promising for data mining and knowledge discovery.展开更多
文摘The information access is the rich data available for information retrieval, evolved to provide principle approaches or strategies for searching. For building the successful web retrieval search engine model, there are a number of prospects that arise at the different levels where techniques, such as Usenet, support vector machine are employed to have a significant impact. The present investigations explore the number of problems identified its level and related to finding information on web. The authors have attempted to examine the issues and prospects by applying different methods such as web graph analysis, the retrieval and analysis of newsgroup postings and statistical methods for inferring meaning in text. The proposed model thus assists the users in finding the existing formation of data they need. The study proposes three heuristics model to characterize the balancing between query and feedback information, so that adaptive relevance feedback. The authors have made an attempt to discuss the parameter factors that are responsible for the efficient searching. The important parameters can be taken care of for the future extension or development of search engines.
文摘An improved decision tree method for web information retrieval with self-mapping attributes is proposed.The self-mapping tree has a value of self-mapping attribute in its internal node,and information based on dissimilarity between a pair of mapping sequences.This method selects self-mapping which exists between data by exhaustive search based on relation and attribute information.Experimental results confirm that the improved method constructs comprehensive and accurate decision tree.Moreover,an example shows that the self-mapping decision tree is promising for data mining and knowledge discovery.
