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.
facility. Automating the transcription of these documents using Optical Character Recognition (OCR) systems is also challenging due to the very complex cursive nature of Urdu text. To overcome these limitations, a keyword spotting based information retrieval system for document images is introduced in this study. The proposed
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
results of keyword search on social photos. Social photos are photos that are posted on social media sites and they usually include posted time and text message as well as photos. It is difficult to know about hot topics in results of keyword search on social photos, because, the huge number of results are returned and they
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
For each treatment plan, patient adherence can be managed, audited, and improved by the Patient Adherence Management System applying Intelligent Keyword (PAMSIK) featuring the use of intelligent keywords to navigate users to the target in-time knowledge and also leverage the collective power - peer learning to
This paper describes a system that conducts search result clustering for several thousands of Web pages, and elaborates cluster labels through keyword distillation. Keyword distillation is a method that properly handles spelling variations, transliterations, synonyms, inclusion relations and word ambiguity, using
This paper proposes an extended vector space model (VSM), which is called M2VSM (meta keyword-based modified VSM). When conventional VSM is applied to document clustering, it is difficult to adjust the granularity of cluster in terms of topic. In order to solve the problem, M2VSM considers meta keywords such as
Text classification is a useful task in text mining. Most researchers employ one word weight type in the text classification. Here, we proposed to build a keyword list by combining several word weights for a rule based multi label text classification. Through this research, we conducted experiments on the term
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
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
Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
Keywords are indexed automatically for large-scale categorization corpora. Indexed keywords of more than 20 documents are selected as seed words, thus overcoming subjectivity of selecting seed words in clustering; at the same time, clustering is limited to particular category corpora and keywords indexed feature
We consider topic detection without any prior knowledge of category structure or possible categories. Keywords are extracted and clustered based on different similarity measures using the induced k-bisecting clustering algorithm. Evaluation on Wikipedia articles shows that clusters of keywords correlate strongly with
In this paper, we address the issue of how to overview the knowledge ofa given query keyword. We especially focus on concerns of those whosearch for Web pages with a given query keyword, and study how toefficiently overview the whole list of Web search information needs of agiven query keyword. First, we collect Web
overlapping communities. Inspired by natural societies, a forum is deemed as a complex network in which all entities (keywords, posts and user) of an online forum are grouped into a series of communities that can share members with each other. To enable this, a kind of keyword association graph is constructed based on the co
images with their surrounding text are collected from a few photo forums to support this approach. The entire process is formulated in a divide-and-conquer framework where a query keyword is provided along with the uncaptioned image to improve both the effectiveness and efficiency. This is helpful when the collected data
This paper proposes a novel method to generate labels for grouping and organizing the search results returned by auxiliary search engines. It has applied statistical techniques to measure the quantities of co-occurrence keywords for forming the label matrix of them, and then agglomerated them into higher-level
The amount of multimedia information is rapidly increasing due to digital cameras and mobile telephones equipped with such devices. To interpret semantic of image, many researchers use keywords as textual annotation. However, current state of the art produces too many irrelevant keywords for images by annotator. They
To improve the web based result there is effective way is to use image re-ranking. Which has been used in many professional search engines like Google and Bing. Given a query keyword the images are retrieved based on that query keyword. By asking the user to select one image from pool of retrieved images other images
avoid unnecessary email reading for that a better email management system is required. Here author used fuzzy logic techniques for email clustering. Extract concept and feature, same feature keyword goes into one cluster if a new keyword is found and not matched with any existing cluster than a new cluster is defined for
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.