A Theme-based Search Technique (original) (raw)

Relevant Page Retrieval and Query Recommendation using Semantic Analysis of Queries

2013

Due to the massive size of the Web and low precision of user queries, search results returned from present web search engines can reach to even hundreds of thousands of documents. Therefore, finding the right information can be a tedious task if not impossible. This paper represents an approach that tries to solve this problem by finding the semantic similarity and similarity metrics to group similar terms using clustering techniques. These similar terms are bind to each other using links in proposed index repository in order to facilitate presentation of results in more compact form and enable the semantic browsing of the results set.

Information Retrieval based on Cluster Analysis Approach

International Journal of Computer Science and Information Technology, 2021

The huge volume of text documents available on the internet has made it difficult to find valuable information for specific users. In fact, the need for efficient applications to extract interested knowledge from textual documents is vitally important. This paper addresses the problem of responding to user queries by fetching the most relevant documents from a clustered set of documents. For this purpose, a cluster-based information retrieval framework was proposed in this paper, in order to design and develop a system for analysing and extracting useful patterns from text documents. In this approach, a preprocessing step is first performed to find frequent and high-utility patterns in the data set. Then a Vector Space Model (VSM) is performed to represent the dataset. The system was implemented through two main phases. In phase 1, the clustering analysis process is designed and implemented to group documents into several clusters, while in phase 2, an information retrieval process ...

Framework for Document Retrieval using Latent Semantic Indexing

2015

Today, with the rapid development of the Internet, textual information is growing rapidly. So document retrieval which aims to find and organize relevant information in text collections is needed. With the availability of large scale inexpensive storage the amount of information stored by organizations will increase. Searching for information and deriving useful facts will become more cumbersome. How to extract a lot of information quickly and effectively has become the focus of current research and hot topics. The state of the art for traditional IR techniques is to find relevant documents depending on matching words in users’ query with individual words in text collections. The problem with Content-based retrieval systems is that documents relevant to a users ’ query are not retrieved, and many unrelated or irrelevant materials are retrieved. In this paper information retrieval method is proposed based on LSI approach. Latent Semantic Indexing (LSI) model is a concept based retrie...