Personal web revisitation by context and content keywords with relevance feedback
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The paper introduces a personal web revisitation technique named webpageprev that utilizes context and content keywords to aid users in recalling previously viewed web pages. It emphasizes the significance of activity context as the best recall cue and discusses methods for acquiring, storing, and utilizing memories for page re-finding. Unlike existing systems that rely solely on chronological access, webpageprev offers a more comprehensive approach by merging contextual and content information.
Personal web revisitation by context and content keywords with relevance feedback
- 1. Personal Web Revisitation by Context and Content Keywords with Relevance Feedback Abstract: Getting back to previously viewed web pages is a common yet uneasy task for users due to the large volume of personally accessed information on the web. This paper leverages human’s natural recall process of using episodic and semantic memory cues to facilitate recall, and presents a personal web revisitation technique called WebPagePrev through context and content keywords. Underlying techniques for context and content memories’ acquisition, storage, decay, an utilization for page re-finding are discussed. A relevance feedback mechanism is also involved to tailor to individual’s memory strength and revisitation habits. Our dynamic management of context and content memories including decay and reinforcement strategy can mimic users’ retrieval and recall mechanism. Among time, location, and activity context factors in WebPagePrev, activity is the best recall cue, and context + content based re-finding delivers the best performance, compared to context based re-finding and content based re-finding. Existing System: In the literature, a number of techniques and tools like bookmarks, history tools, search engines, etc systems have been developed to support personal web revisitation. In existing search engine, and fetched relevant previously viewed results from its cache. The newly available results were then merged with the previously viewed results to create a list that supported intuitive re-finding and contained new information. For Ex: History Tools. History tools of web browsers maintain user’s accessed URLs chronologically according to visit time (e.g., today, yesterday, last week, etc.), and accessed page titles and contents. Search Engines. How search engines are used for re-finding previously found search results. It explored the differences between queries that had substantial/minimal changes between the previous query and the revisit query. Disadvantages:
- 2. No search for web revisitation. Depends on only time and date. Proposed System: Inspired by the psychological findings, this paper explores how to leverage our natural recall process of using episodic and semantic memory cues to facilitate personal web revisitation. We present a personal web revisitation technique, called WebPagePrev, that allows users to get back to their previously focused pages through access context and page content keywords. Underlying techniques for context and content memories’ acquisition, storage, and utilization for web page recall are discussed. Preparation for web revisitation. When a user accesses a web page, which is of potential to be revisited later by the user (i.e., page access time is over a threshold), the context acquisition and management module captures the current access context (i.e., time, location, activities inferred from the currently running computer programs) into a probabilistic context tree. Advantages: New technology for personal web revisitation. Depend on both context and content keywords. SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS: Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
- 3. SOFTWARE REQUIREMENTS: Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8 Implemented by Development team : Cloud Technologies Website : http://www.cloudstechnologies.in/ Contact : 8121953811, 040-65511811