Deepti Gupta

Retrieval of Web Documents Using a Fuzzy Hierarchical Clustering

ABSTRACT The World Wide Web has huge amount of information that is retrieved using information retrieval tool like Search Engine. Page repository of Search Engine contains the web documents downloaded by the crawler. This repository contains variety of web documents from different domains. In this paper, a technique called “Retrieval of Web documents using a fuzzy hierarchical clustering” is being proposed that creates the clusters of web documents using fuzzy hierarchical clustering. Keywords Search Engine, Web documents, Fuzzy Hierarchical Clustering Indexer 1. Introduction WWW [01, 02 and 04] is a huge repository of information consisting of hyperlinked documents spread over the internet. The size of the web as on February 2010 stands at around 35 million pages. For a user, it is practically impossible to search through this extremely large database for the information needed by him. Hence the need for Search Engine (see fig. 1) arises. The search engine uses crawlers to gather information and stores it in database maintained at search engine side. For a given users query the search engine searches in the local database and very quickly displays the results. The huge amount of information [05] is retrieved using data mining tools. Classification, Clustering and Association tools etc. are used for data mining technique. Clustering plays a key role in searching for structures in data. As the number of available documents nowadays is large, hierarchical approaches are better suited because they permit categories to be defined at different pensiveness work about levels. The problem of clustering in finite set of data is to find several cluster centers that can properly characterize relevant classes of finite set of data such that degree of association is strong for data within blocks of the partition and weak for data in different blocks. When the weakness of a crisp partition of finite set of data is replaced with a fuzzy partition, this area is known as fuzzy clustering. Fuzzy clustering is a relevant technique for information retrieval. As a document might be relevant to multiple queries, this document should be given in the corresponding response sets, otherwise, the users would not be aware of it. Fuzzy clustering seems a natural technique for document categorization. There are two basic methods of fuzzy clustering, one which is based on fuzzy c-partitions, is called a fuzzy c-means clustering method and the other, based on the fuzzy equivalence relations, is called a fuzzy equivalence clustering method.

Performance Evaluation of Routing Protocols for WSNs Based on Energy-aware Routing with different Radio Models

In this paper, we present the simulation results of the comparative investigation of the performance of the wireless sensor network routing protocols based on different routing objective: energy-aware routing using PROWLER and RMASE. Our simulation results indicate that the energy-aware routing objective increases the network lifetime for the Adaptive Tree, Constrained Flooding and Real-Time routing protocols than the default shortest path routing objective for Normal Radio Model, Radio Model with SINR, Radio Model with Rayleigh Fading and Radio Model with Rician Fading. It has been concluded that the network lifetime is longer with energy-aware as compared to shortest path routing objective. The energy-aware routing objective o = emax/(e+1) gives better lifetime than o = (k х u) + 1 for CF and AT routing protocols. It has been shown that without changing the routing strategy and by using the right routing metrics routing protocols can be made energy-aware to increase lifetime.

Comparative Investigations and Performance Evaluation for Multiple-Level Association Rules Mining Algorithm

This paper focuses on the comparative investigation and performance evaluation of the ML_TMLA algorithm that generates multiple transaction tables for all levels in one database scan with that of ML_T2L1 and ML_T1LA algorithms. The performance study has been carried out on different kinds of data distributions (three synthetic and one real dataset) and thresholds that identify the conditions for algorithm selection. The AR Tool has been used for the experimental and comparative evaluation of the proposed algorithm with other algorithms.

Performance evaluation of constrained flooding routing protocol for WSNs based on path loss exponent

In this paper, we present the simulation results of the comparative investigation of the performance of the constrained flooding routing protocol (CF) based on different path loss exponents using PROWLER. Our simulation results indicate that the path loss exponent 4.10 increases the network lifetime for the CF routing protocol than the path loss exponent 3.0.