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.
particular category. Search is truly ``local'' in the sense that keyword relevance is not global, but specific to the category. In contrast to using a search engine, users can guide the exploration engine with relevance feedback alone without entering keywords.
Web of world facilitates search results on massive collection of data using Internet. While obtaining search results corresponding to a particular search query, authentication of search results becomes an important question, as different sources contribute data in every moment which are stored in (un)trusted third
Web information access today primarily relies on search engines. Current search engines cannot make index to the pages which are generated automatically by the back -- end databases called invisible web or deep web. The information is hidden behind HTML forms and is only available in response to user's request. In
Web pages for search engine. First we describe a scheme based on semantic keywordscombined with sentence overlapping, and then show an implemented prototype, with the experimental results that suggest the prototype work well under a proper setting.
Conventional supervised methods for image categorization rely on manually annotated (labeled) examples to learn good object models, which means their generality and scalability depends heavily on the amount of human effort available to help train them. We propose an unsupervised approach to construct discriminative
challenge for the user is to come up with a set of search terms/keywords/sentence which is neither too large (making the search too specific and resulting in many false negatives) nor too small (making the search too general and resulting in many false positives) to get the desired result. No matter, how the user specifies the
The problem of automatically extracting the most interesting and relevant keyword phrases in a document has been studied extensively as it is crucial for a number of applications. These applications include contextual advertising, automatic text summarization, and user-centric entity detection systems. All these
The total information available on WWW (World Wide Web) is huge and is increasing at lightning speed. Existing web is dominated by Search Engines which are running on keyword based search system which in turn leads to wastage of end user's precious time if he do not know the key terms which are utilized to index
This paper proposes a systematic full text search on document using a combinedkeyword and structural similarity of documents under consideration. The approach operates in two steps. The first step uses a set of designated keywords to acquire potential desired documents by means of an open source tool. The second step
auctions’ performance. Few papers directly predict the ROI of a keyword portfolio. This approach effectively echoes advertisers’ expectation for a keyword auction by choosing the right keywords and bids to achieve the desired outcome. The building blocks of the prediction model, such as bid and rank, are
performance on cultural keywords, we conducted a survey using some Ghanaian's terms as our case study on the basis of trust, relevance and accessibility. Surprisingly, the results showed that several documents from external sources (regions outside the location of that culture) had higher rankings against that of the originating
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
. Extracted Web knowledge is useful not only for evaluation (quality, trustworthiness etc.) of search results, but also for improving conventional Web search, such as supporting user's recall of vocabulary (query keywords) and re-ranking of search results. The proposed extraction mechanism is based on the ideas of the usage of
quickly to help such evolution and in many situations the Web Services application is driving businesses and dictating a new way of doing business. In this paper, we present an ideal model for developing web servers for small organizations by including search engine optimization techniques such as the best set of keywords
automatic transcription of a spoken document using a speech recognizer. The difficult point of this task is that the automatic transcription contains many recognition errors, therefore we cannot trustkeywords extracted from the automatic transcription using conventional method such as tfmiddotidf. To solve this problem, we
This paper describes the application of agents to automate information exchange for digital preservation. Agents are able to recommend preservation solutions and also apply them to different preservation situations. Trust models for question-routing and answer ranking that are implemented by means of agents, show
With the rapid rise in the number of weblogs, or blogs, on the World Wide Web (WWW), there is a growing need to be able to quickly search for discussion on specific topics. While keyword searches using tools such as Google or Technorati can yield useful results, we run into the problem of having to enter
Purely keyword-based text search is not satisfactory because named entities and WordNet words are also important elements to define the content of a document or a query in which they occur. Named entities have ontological features, namely, their aliases, classes, and identifiers. Words in WordNet also have ontological
relevant and desired answer. Even though an image would represent a set of Thousands of keywords and phrases it give rise to image ambiguity just Word Sense Disamguity (WSD). It's very challenging to map user keyword query to retrieve image as answer, as relevance depends on user perception and intent. Web-Image search
such as children. It may be very intricate for children to search their desired content effectively using the traditional ‘keyword based’ search mechanism. They may fail to map the desired concept into appropriate keywords. To circumvent this situation, Faceted navigation is proposed as an effective
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.