The integration of the classical Web (of documents) with the emerging Web of Data is a challenging vision. In this paper we focus on an integration approach during searching which aims at enriching the responses of non-semantic search systems (e.g. professional search systems, web search engines) with semantic information, i.e. Linked Open Data (LOD), and exploiting the outcome for providing an overview...
the semantic units from text according to the keywords representing users’ interests and can organise semantic units into facets reflecting certain aspects of a text. The mechanism can display facets of a text with a set of operations. The proposed mechanism considers human reading process. With this mechanism, readers
effective in terms of better precision. Proposed method makes use of keyword clusters for query expansion. Visual features are used for detecting duplicate images in proposed method. Removing duplicates leads to further improve in precision and recall in retrieval result
paper, algorithm is defined to improve relevancy of result based on webpage keyword ratio. In result analysis, result of proposed method is compared with deferent algorithms such as PageRank and Topic Distillation with Query Dependent Link Connections and Page Characteristics result.
An individual's problem space has been identified as important in problem solving. A problem space is a person's inner representation of the task after extracting critical components in the external problem task. This paper proposes a study to probe whether there are different problem spaces for efficient and inefficient Web information searchers. The questions will be answered quantitatively using...
The paper presents a novel benefit based query processing strategy for efficient query routing. Based on DHT as the overlay network, it first applies Nash equilibrium to construct the optimal peer group based on the correlations of keywords and coverage and overlap of the peers to decrease the time cost, and then
Given a set of keywords, we find a maximum Web query (containing the most keywords possible) that respects user-defined bounds on the number of returned hits. We assume a real-world setting where the user is not given direct access to a Web search engine's index, i.e., querying is possible only through an interface
Textual web pages dominate web search engines nowadays. However, there is also a striking increase of structured data on the web. Efficient keyword query processing on structured data has attracted enough attention, but effective query understanding has yet to be investigated. In this paper, we focus on the problem of
This paper discusses techniques for improving the performance of keyword-based web image queries. Firstly, a web page is segmented into several text blocks based on semantic cohesion. The text blocks which contain web images are taken as the associated texts of corresponding images and TF*IDF model is
Semantic and keyword web based technique is becoming a generic issue in an application of Information Retrieval (IR). Most of the researchers used different web techniques for finding relevant information and find the keyword based search, which are not able to fetch the relevant search result because they do not know
In this paper, we address the issue of how to overview the knowledge of a given query keyword. We especially focus on concerns of those who search for Web pages with a given query keyword, and study how to efficiently overview the whole list of Web search information needs of a given query keyword. First, we collect
Inspired by the great success of information retrieval (IR) style keyword search on the web, keyword search on XML has emerged recently. The difference between text database and XML database results in three new challenges: 1) Identify the user search intention, i.e., identify the XML node types that user wants to
Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
quality of information retrieval. The contributions of our research are twofold. First, the existing ranking algorithms of search engine are classified. And we extend expression of queries by “keyword and ”, instead of keywords only. Second, a new ranking algorithm based on user feedback and semantic tags is
Portable personalization service has been proved very useful in the sharing and reusing of user personalized profiles among different platforms. We present an approach of a Web requesting framework for portable personalization service based on iterative profiling algorithm with time unit of weighted keywords and give
database, cannot be applied to Web search. We propose a new method to support Web query refinement. Our methods is based on local analysis which clustering the search result. Unlike other clustering-base approaches, we take into consideration the distance between keywords, and guarantee no information loss. A Web search
Search engines are one of the most powerful tools in the Web world today for data retrieval and exploration. Most search engines identify the key word in the sentence or phrase or list of words given by the user and starts mining the Web for the occurrence of keyword in the Web pages. Quite often searching for the key
In this paper, we address the issue of how to overview the knowledge ofa given query keyword. We especially focus on concerns of those whosearch for Web pages with a given query keyword, and study how toefficiently overview the whole list of Web search information needs of agiven query keyword. First, we collect Web
audiences and website's competitors when analyzing keywords; (2) insert keywords into web text that will appear on search engine results pages, and (3) involve their web content and websites with other web content creators. Implications: Because successful search engine optimization requires considerable time, professional
-processing of Web search results have been extensively studied to help user effectively obtain useful information. This paper has basically three parts. First part is the review study on how the keyword is expanded through truncation or wildcards (which is a little known feature but one of the most powerful one) by using
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.