The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A model of the precursors of intention to use in online keyword searching is presented and empirically tested with data collection. Analysis of the data 331 participants, utilizing structural equation model (SEM), supported most of the predictions. Language anxiety, perceived ease of use, perceived usefulness
Internet is becoming an increasingly important platform for ordinary life and work. It is expected that keyword extraction can help people quickly find hot spots on the web, since keywords in a document provide important information about the content of the document. In this paper, we propose to use text clustering
Peer-to-peer approaches bring one perfect alternative for the Web content search. However, how to search and retrieve the data based on the content query is still an open problem for peer-to-peer systems. In this paper we propose History-based Multi-keywords Search(HMS) in unstructured peer-to-peer systems, which only
Text keywords at different semantic levels have different semantic representation abilities. Although words have been organized by semantic dictionaries (e.g. WordNet) with exact semantics, the dictionaries can not be constructed automatically by machine and there are still many words which are not included in the
classic statistical method for sentence alignment, we propose an improved approach to align the initial bilingual resources, in which two factors, bilingual keyword pairs and matching patterns are introduced. Experimental results show that our sentence aligner supported by the new approach achieves performance enhancement by
Granular computing is an emerging technology. This paper summarizes its applications to the Web. A high frequent co-occurring ordered set of keywords is called a keyword set;it represents some concept in the given document set. These concepts forms a simplicial complex of concepts,which is regarded as a knowledge base
proposed a collective collaborative tagging (CCT) service architecture in which both service providers and individual users can merge folksonomy data (in the form of keyword tags) stored in different sources to build a larger, unified repository. We have also examined a range of algorithms that can be applied to different
The speedy evolution in web environment and progression in technology have led us to access and manage tremendous images easily in various areas. Current internet image search engines purely trust on the text based information around the images. Keywords supplied by user can not specify content of images exactly
In this research, we used a proxy server to search for information related to the userpsilas browsed Web pages. From the records of the proxy server we constructed a profile of the userpsilas browsing habits. At the end of the userpsilas search subsystem, we will use content based concept to extract keywords to obtain
Using disaggregated data from a Chinese search engine we jointly model ad rank and performance for hospitality related keyword searches. As a result of our modeling framework we can better determine the optimal keyword bidding strategy for an advertiser given the search engine's control over ad rank. Our approach
some problems, they tend to retrieve the information from the Web search engines. Many business search engines are efficient at identifying the best web sites for any given keyword query. Unfortunately, the information on the web is not always correct. Moreover, different web sites often provide different information on a
thesauruses, categories, ontologies, and folksonomies. A statistical semantic association model is proposed to integrate different semantic models, represent heterogeneous semantic information, and support semantic relevance computation. A focused crawling framework is developed which adopts both keyword based contents and
The insufficiency of consumer's trust is one of bottlenecks to China online shopping, and now most Web sites resort to the renowned third party or trust displaying mechanism to promoting consumer's trust. However, whether the two kinds of trust promotion strategies above have the same effect? And whether their own attributes and assurance contents have the significant influence on consumer's trust?...
Adult image detection plays an important role in Internet pornographic information detection and filtering. By analyzing the shortcomings of existing pornographic image detection algorithms depending only on image content or keywords of text, a new adult image detection algorithm fusing image semantic features and
time. Comparing the 'like' query in the standard SQL in relational databases, which can not decide the similarity according users' interests when keywords appear in several different fields, a novel similarity evaluation is given in algorithm of the personalized recommendation. Using the method, a personalized digital
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.