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.
Processing short texts is becoming a trend in information retrieval. Since the text has rarely external information, it is more challenging than document. In this paper, keyword clustering is studied for automatic categorization. To obtain semantic similarity of the keywords, a broad-coverage lexical resource WordNet
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
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
Currently keyword search is a prominent data retrieval method for the Web because the simple and efficient nature of the keyword processing allows it to process a large amount of information with fast response. However, keyword search approaches do not formally capture the clear meaning of a keyword query and fail to
Web-scale image search engines (e.g., Google image search, Bing image search) mostly rely on surrounding text features. It is difficult for them to interpret users' search intention only by query keywords and this leads to ambiguous and noisy search results which are far from satisfactory. It is important to use
apps via a set of keywords. MARK then lists the reviews most relevant to those keywords for further analyses. It can also draw the trends over time of the selected keywords, which might help the analyst to detect sudden changes in the related user reviews. To help the analyst describe her interests more effectively, MARK
focused web crawler under the EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organized crime). The crawler allows 1. to look for documents starting from a URL until a parametric depth of levels - also specifying a keyword that has
Service discovery is a mechanism for finding services, the existing service discovery mechanisms offer low retrieval precision and recall. The current problem with service inventories such as UDDI is the retrieval process which associated with the search engines that support only syntactic, keyword-Oriented search
Most researches on Image Retrieval (IR) have aimed at clearing away noisy images and allowing users to search only acceptable images for a target object specified by its object-name. We have become able to get enough acceptable images of a target object just by submitting its object-name to a conventional keyword
A mind map is a diagram used to represent words, ideas, or other items linked to and arranged around a central keyword or idea. Mind maps are used to generate, visualize, structure, and classify ideas, and as an aid in organization, study, project management, problem solving, decision making, and writing. It has been
understanding of domain in which semantics of data is machine understandable. Second, we make in Raspberry Pi an interface which has the capability to recognize speech queries and give an oral response. Our interface analyzes each speech query, convert speech to text and extract keywords from the text. Later, these keywords are
to the purchase page of the product or the service being promoted. The paper proposes a method that suggests the keywords of a web page based on the frequent terms in a web page while including the lexical relationship (synonyms) of these words. An experiment is executed to validate the method while the method's result
input language of the submitted document and English as a target language of similar, possibly plagiarised documents. In this system we shorten the query document by utilising fuzzy swarm-based summarisation approach. Our point of view is that using the summary will give us the most important keywords in the document
and user behaviors are indexed and managed; Based on the user's input keywords and navigation context, a group of relevant services are dynamically searched, ranked and recommended for facilitating future navigations; the service navigation is smoothed by a web2.0 style exploratory user interface. A prototype system is
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.