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...
Text analysis of a web page is more difficult than the analysis of the text of normal document due to the presence of additional information, such as HTML structure, styling codes, irrelevant text, and presence of hyperlinks. In this paper, we propose an unsupervised method to extract keywords from a web page. The
With the increase of information scale of web events on the time, it is extremely difficult and challenging to grasp the semantics of web events artificially, because of the limitation of the time and energy of human beings. Herein, we propose a method to map the web event to keyword level association link network
Language Model (LM) constitutes one of the key components in Keyword Spotting (KWS). The rapid development of the World Wide Web (WWW) makes it an extremely large and valuable data source for LM training, but it is not optimal to use the raw transcripts from WWW due to the mismatch of content between the web corpus
distances in a multidimensional scaling space. In this study, we introduce an example of a 3-D multimedia space using the Associated Keyword Space (ASKS) and demonstrate similarity relationships between various sources of data in this space.
This paper presents a new keyword extraction algorithm for Chinese news Web pages using lexical chains and word co-occurrence combined with frequency features, cohesion features, and corelation features. A lexical chain is an external performance consistency by semantically related words of a text, and is the
A keyword choice and analysis approach in SEO is studied to deal with the issues such as low efficiency, poor reliability and instability optimization in artificial SEO processing in this paper. A keyword expansion method is proposed by reversing search engine's related search keywords to meet user's requirements
In this paper, we propose a novel image search scheme is contextual image search with keyword input. It is different from conventional image search schemes. it consist of three step process, first one is context extraction to distinguish the image entities of the same name, second step is conceptualization to convert
integrate information from multiple interrelated pages to answer keyword queries meaningfully. Next-generation web search engines require link-awareness, or more generally, the capability of integrating correlative information items that are linked through hyperlinks. In this paper, we study the problems of identifying the
Language model adaptation using text data downloaded from the WWW is an efficient way to train a topic-specific LM. We are developing an unsupervised LM adaptation method using data in the Web. The one key point of unsupervised Web-based LM adaptation is how to select keywords to compose the search query. In this
keyword driven crawling with relevancy decision mechanism and uses Ontology concepts which ensures the best path for improving crawler's performance. This paper introduces extraction of URLs based on keyword or search criteria. It extracts URLs for web pages which contains searched keyword in their content and considers such
system called "WebAngels filter" which uses textual and structural content-based analysis. These analysis are based on a violent keyword dictionary. We focus our attention on the keyword dictionary preparation, and we demonstrate that a semi-automatic keyword dictionary can be used to improve the filtering efficiency of
Search engines on the Web have popularized the keyword-based search paradigm, while searching in databases users need to know a database schema and a query language. Keyword search techniques on the Web cannot directly be applied to databases because the data on the Internet and database are in different forms
Nowadays the existing search engines are always lack of the consideration of personalization. They display the same search results for different users despite their differences in interesting and purpose. In order to solve this problem, this paper introduces a new method of using keyword query series to express the
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
Search engines prominently use inverted indexing technique to locate the Web pages having the keyword contained in the users query. The performance of inverted index, fundamentally, depends upon the searching of keyword in the list maintained by search engines. This paper presents a new technique for keyword searching
The Net and Web technologies effectively and efficiently accelerate secure e-commerce transactions by reducing what is known as the Total Cost of Ownership (TCO) for commercial activities that a business normally incurs. Businesses choose a keywords advertising that best describes their main Web pages. The pages are
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
. In this paper, we propose a web page-oriented and keywords-based approach to address this problem. Our approach includes two key components: keyword similarity measurement and keyword similarity based user segmentation. These two components serve as plugins and can be replaced with better algorithms or measurements
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”.