Twist
1 like546 views
Twist is an open world information sharing network aimed at improving the way users search for and share knowledge across common interests, bridging the gap between traditional knowledge portals and social networking platforms. The platform allows users to enroll in categories of interest, receive updates on relevant articles, and connect with others working on similar projects while leveraging cloud computing for data organization. Key features include user activity tracking, tailored recommendations, and integration using a LAMP stack for its development.
Twist
- 1. “Twist”- An Open World Information Sharing Network Mayur Ahir, Harsh Gadhia, Jatin Patel Students, Final Year, Information Technology, K. J. Somaiya Institute of Engineering & Information Technology mayur@mayurahir.com gadhiaharsh@yahoo.co.in jatinhpatel@yahoo.co.in I. Detailed Statement of Problem Today we have immense amount of knowledge present of various Knowledge Portals either on a specific field e.g. Cisco.com or in form of collection of categories e.g. Technorati.com We also, have many platforms which support the Social Networking and allow a large amount of people to come together e.g. Facebook.com, Orkut.com. But the major problem is that, the Knowledge Portals can provide information to an individual but there is no facility to know other people or the group of peoples who are looking for same information although this can be very useful in order to increase the knowledge. Total opposite problem is faced by Social Networking Platforms where people can know each other but cannot share their knowledge. People researching on a common field of interest search for the latest updates on various sites, these might be based on their preference or likes. These websites can be either a Knowledge Portal or Forums which provides recent updates. There might be situation under which different people working on same project or a same field visits these sites irrespective of each other. Similarly a user searching for information may find visiting and searching on various sites irritating and time consusming. Likewise many users searching for same information on web and exploring the search engines leads to waste of resources and time. II. Introduction Twist is an Open World Information Sharing Network which provides a platform to the users searching information on the same project that directly publishes the new updates for a desired category or group of categories to the people who had enrolled as that category for their Personal interest. It also asks the users to make friends on the web searching for the same articles by selecting the interested categories; the application provides the user with the latest updates from the various sites. If the user needs more information then user will be redirected to the sites providing latest news and updates. Here the basic aim of Twist which is “Instead users searches information, information searches users” Is defined. Till now we have seen use of the Cloud computing only in very large Systems which are not available for general public. But use of same for Twist as a Backbone enables to tracks the user’s location and hence routes the user’s request to the geographically nearest available Server. This will also help to publish the local information based on users’ location. “Twist is not a social networking platform but it is being developed for collaborating and searching knowledge on the web.” Information will be categorized on the basis of following criteria
- 2. Training in: • • • 2. Software & Hardware, Communication skills, Placements, etc. From Users reading articles to Activity Tracing Database. Researches in: • • • • Touch screens, Media, Networks, Multimedia, etc. Technologies in: • • • IT, Gadgets, Embedded systems, etc. III. Architecture A. Data Flow Diagrams : 1. From External sites to our Database using Standard XML and RSS. DFD: Fig. 3 : Data Flow Diagram B. Control Flow Diagrams 1. 2. 3. Fig. 1 Data Flow Diagram 4. Level 1 DFD. 5. Fig. 2 : Level 1 Data Flow Diagram When user registers selects Interested Categories and according to these articles are shown. Next time onwards when user visits, show latest updates on selected categories. If user selects to Twist the article / category than update the Activity Tracker also for an individual article. Depending upon the articles read by users; suggest “Indirect Buddies” (i.e. those who shares common interests e.g. Research Groups). There is also an additional feature which allows making of “Direct Buddies” (i.e. which are known directly e.g. College Friends).
- 3. 3. Fig. 3 : Control Flow Diagram IV. Front End : PHP + jQuery Front End and Back End Best Open Source Programming Language for developing Dynamic Applications. Has very good online community support. It also allows development of applications with object oriented concepts. jQuery is JavaScript based API which allows to develop AJAX integration with any programming language used to provide a good OOUI and enables client site computations. 4. Back End : MySQL One of the most popular Open Source SQL platforms for developing large scale databases. It has also got huge amount of online support. University of Illinois (UIUC), Karlsruhe Institute of Technology, the Info-comm Development Authority (IDA) of Singapore, the Electronics and Telecommunications Research Institute (ETRI) in Korea, the Malaysian Institute for Microelectronic Systems (MIMOS), and the Institute for System Programming at the Russian Academy of Sciences (ISPRAS). Facebook was launched in February 2004 by Harvard undergrad students as an alternative to the traditional student directory. Its popularity quickly spread to other colleges in the US by word of mouth, and the site now registers close to 15M monthly UVs and over 6B page views per month. Facebook has completed two rounds of venture financing at very high valuations, the first at a valuation of ~$100M and the second at ~$550M (valuations are unconfirmed). These valuations were driven by the multiple acquisition offers that Facebook has reportedly turned down (the latest was a rumored $750M offer). Facebook is already generating significant revenue, so despite all the valuation and web traffic metric hype, it has also established a very real business. Knowledge Portals like CNet.com, technorati.com, tech2.com provides useful content but not sharing. Facebook had its initial success with college students by providing an information service that was not available offline – an interactive student directory containing each student’s class schedule and social network. Before Facebook added the feature sets it has today, it was simply a more complete student directory. Facebook did not create a community where one never existed before; rather they provided an important information and communication service to a per-existing offline community. VI. V. Literature Survey 1. 1. Recent research has shown as much as 85% to 90% of 2. internal IT organizations are moving or have already moved to a service-centric model for delivering IT value. Rather than focusing on infrastructure components like servers and storage, IT organizations today are concentrating on end-to-end services including email and order management. In July 2008, HP, Intel Corporation and Yahoo! announced the creation of a global, multi-data center, open source test bed, called Open Cirrus, designed to encourage research into all aspects of cloud computing, service and data center management. Open Cirrus partners include the NSF, the 2. 3. IEEE Research Papers “Rich Media and Web 2.0”, Edward Chang, Ken Ong, Susanne Boll, Wei-Ying Ma, Proc. 17th International Conference on World Wide Web, 2008, pp. 1259-1259. “Extracting knowledge from the World Wide Web”, Monika Henzinger, Steve Lawrence, Mapping Knowledge Domains, 2003. “Collaborative Filtering for Orkut Communities: Discovery of User Latent Behavior”, Wen-Yen Chen, Jon Chu, Junyi Luan, Hongjie Bai, Edward Chang, 18th International Conference on World Wide Web (WWW), 2009, pp. 681-690.
- 4. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. “A social network caught in the Web”, Lada A. Adamic, Orkut Buyukkokten, Eytan Adar, First Monday, vol. 8 (2003). “Personalized News Recommendation Based on Click Behavior”, Jiahui Liu, Elin Pedersen, Peter Dolan, 2010 International Conference on Intelligent User Interfaces. “How opinions are received by online communities: A case study on Amazon.com helpfulness votes”, Cristian Danescu-Niculescu-Mizil, Gueorgi Kossinets, Jon Kleinberg, Lillian Lee, Proceedings of the 18th International Conference on World Wide Web, WWW 2009, Madrid, Spain, April 20-24, 2009, pp. 141-150. “Information extraction meets relation databases”, Davood Rafiei, Andrei Broder, Edward Chang, Patrick Pantel, CIKM '09: Proceeding of the 18th ACM conference on Information and knowledge management, 2009, pp. 897-897. “Information arbitrage across multi-lingual Wikipedia”, Eytan Adar, Michael Skinner, Daniel S. Weld, WSDM '09: Proceedings of the Second ACM International Conference on Web Search and Data Mining, 2009, pp. 94-103. “Current trends in the integration of searching and browsing”, Andrei Z. Broder, Yoelle S. Maarek, Krishna Bharat, Susan T. Dumais, Steve Papa, Jan O. Pedersen, Prabhakar Raghavan, WWW (Special interest tracks and posters), 2005, pp. 793. “Privacy-preserving indexing of documents on the network”, Mayank Bawa, Roberto J. Bayardo, Rakesh Agrawal, Jaideep Vaidya, The VLDB Journal, vol. 18 (2009), pp. 837-856. “Lightweight Feedback-Directed Cross-Module Optimization”, Xinliang David Li, Raksit Ashok, Robert Hundt, Proceedings of International Symposium on Code Generation and Optimization (CGO), 2010. “Parallel algorithms for mining large-scale rich-media data”, Edward Y. Chang, Hongjie Bai, Kaihua Zhu, MM '09: Proceedings of the seventeen ACM international conference on Multimedia, 2009, pp. 917-918. “The Space Complexity of Processing XML Twig Queries over Indexed Documents”, Mirit Shalem, Ziv Bar-Yossef, Proceedings of the 24th International Conference on Data Engineering (ICDE), 2008, pp. 824-832. VII. 1. 2. Algorithms Used Unstructured Data Mining Algorithm. Users Activity Tracking. 3. Personalized user recommendations. VIII. Implementation Plan 1. Using standard LAMP (Linux, Apache, MySQL, and PHP) Stack. 2. With direct integration of any PHP Framework and IDE(integrated development environment ). 3. Enabling User Side AJAX. 4. User Registration and Login using SSL. IX. Conclusions By developing a new field known as Information Networking we can derive following advantages of Twist. 11 Reduces time and resources consumption. 11 Unstructured content from various sites is formatted in standard structure and categories. 11 Aggregation of information from various websites and users searching same information. 11 Easy to use since two most famous triads of web viz. Information Portals and Social Networking are submerged. 11 Cloud computing based. 11 Use of Open sourced software APIs. 11 People working on the same projects can mutually share data which is automatically facilitated by Twist.