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.
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 recent years, user generated content services have become popular. The authors are interested in online novel services. Classification of online novels is difficult because keywords and genre are assigned by the author of the novel without control. In order to overcome the problem faced when category classifying
As personalization technologies are widely used, preference extraction is becoming important. In this work, we propose a preference extraction method on the basis of applications that are installed on a user's smart device. In this method, keywords are extracted from descriptions of the installed applications on an
Co-clustering is a promising technique for summarizing cooccurrence information such as purchase history transactions and document-keyword frequencies. A close connection between fuzzy c-means (FCM) and Gaussian mixture models (GMMs) have been discussed and several extended FCM algorithms, which are induced by the
activities, such as identification of growing researchers and supervisors. In previous paper we proposed a visualization system for co-authorship networks, which provides the function for identifying research areas and that for identifying temporal variation of both network structure and keyword distribution. This paper
In this paper, we analyzed the influence of geographical area (Jordan) and a local culture on website search engine ranking, and identify the effect and the relationship of the local society keywords in increasing website ranking. Our analysis provides a foundation for understanding the search engine optimization in
Feature location is a human-oriented and information-intensive process. When performing feature location tasks with existing tools, developers often feel it difficult to formulate an accurate feature query (e.g., keywords) and determine the relevance of returned results. In this paper, we propose a feature location
A user's location information is commonly used in diverse mobile services, yet providing the actual name or semantic meaning of a place is challenging. Previous works required manual user interventions for place naming, such as searching by additional keywords and/or selecting place in a list. We believe that applying
the industry. Much of what is available tells that information such as cookies and browsing history are used to target customers, associating keywords with specific groups of inventory. We designed and conducted a web-based shopping experiment with fifty participants to observe how people of different backgrounds and
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.