There are various types of user profile acquisition approaches, which are classified into five groups: (1) data mining, (2) statistics and network analysis, (3) Information retrieval, (4) machine Learning and (5) Cognitive. Most of the methods are dealing with static Websites except a couple of methods that can be applied on dynamic Websites (Nasraoui & Rojas, 2003).
The method employs data mining techniques such as a frequent pattern and reference mining found from (Holland et al., 2003; KieBling & Kostler, 2002) and (Ivancy & Vajk, 2006). Frequent and reference mining is a heavily research area in data mining with wide range applications for discovering a pattern from Web log data to obtain information about navigational behavior of the users. The frequent and reference patterns from their research can be classified into page sets, page sequences and page graphs.
The used of descriptive statistics to extract knowledge from Web log has been introduced by Srivastava, Deshpende & Phang (2000), by analyzing the session files and perform statistics of user interaction such as frequency, mean, and median on variables i.e. page views, viewing time and length of a navigational path. Additionally, Web logs file analysis using statistical approach proposed by Stermsek et al.(2007) allow for a broader perception of user behavior and potential to improve user profiling. Their approach includes several methods such as statistical inference, graph analysis and profile generation: (1) Statistical inference is from pre-processed web log data, (2) structure analysis for selecting a certain structure on the website (e.g., soccer news), then perform structure of the Website related to user’s interest on soccer news and (3) Graph analysis o...
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... of Web Personalization to customize services (e.g. content and items) to the needs and prefer user or group of users. This is clear in the adaptive Web, where acceptance is to meet the needs of users (Agrawal, 1999; Mobasher et.al., 2000).
There are different approaches for representing user profiles. For example, Mobasher et.al. (1999) and Kang et.al. (2001) analyze URLs to get the user’s preference from Web logs. Additionally, Mobasher et.al. (1999) combined Web usage mining and content mining for effective personalization. Shokry and Ajinanth (2006) used clustering techniques to obtain user’s preference.
From literature review, the method of representing UP can be classified in three methods: (1) graph representation, (2) tree, (3) XML, and (4) RDF. The following briefly described method of UP representation in Web personalization, as presents in Table 8.
Personalisation enables the service user to find the right way for them to participate in the delivery of their care. Therefore the service user receives support that is most suited to them.
Wallace, Jonathon. (1997). Labelling, rating and filtering systems on the Internet. [Online]. Available: http://www.spectacle.org/cda/rate.html. [1997, Sep. 02].
Providing Full-Text Access to Eric Digest. n.p. 2003. The 'Secondary' of the 'Secondary' of the Web. The Web. The Web.
Usability is a critical portion of web design that one must be ever mindful of when constructing websites. Whether creating a personal web space or building multiple pages for a large corporation, it is the burden of the designer to guarantee people can access that content. According to the United Nations, disabled people compose roughly 10 percent of the world’s population (United Nations, 2010). Many regulations and standards have been set forth to provide disabled people with the same opportunities to access content available on the World Wide Web, as it is most of the World’s population.
Web. The Web. The Web. 9 May 2012. Lipking, Lawrence I, Stephen Greenblatt, and M. H. Abrams.
Various web-based companies have developed techniques to document their customer’s data, enabling them to provide a more enhanced web experience. One such method called “cookies,” employs Microsoft’s web browser, Internet Explorer. It traces the user’s habits. Cookies are pieces of text stored by the web browser that are sent back and forth every time the user accesses a web page. These can be tracked to follow web surfers’ actions. Cookies are used to store the user’s passwords making your life easier on banking sites and email accounts. Another technique used by popular search engines is to personalize the search results. Search engines such as Google sell the top search results to advertisers and are only paid when the search results are clicked on by users. Therefore, Google tries to produce the most relevant search results for their users with a feature called web history. Web history h...
Employees are not the only people whose information interest companies. To a far greater extent, businesses are looking to gather data on their users and the market in general. User data collection has become one of the most important components of market research. For example, online retailers can use data collected from a consumer’s purchase to target advertising on products that the consumer is most likely to buy....
There is a debate between the benefits and potential informational privacy issues in web-data mining. There are large amount of valuable data on the web, and those data can be retrieved easily by using search engine. When web-data mining techniques are applied on these data, we can get a large number of benefits. Web-data mining techniques are appealing to business companies for several reasons [1]. For example, if a company wants to expand its bu...
In today’s fast paced technology, search engines have become vastly popular use for people’s daily routines. A search engine is an information retrieval system that allows someone to search the...
THURAISINGHAM, BHAVANI. (2003). Web Data Mining and Applications in Business Inteligence and Counter-Terrorism.Taylor & Francis.http://www.myilibrary.com?id=6372.
“The Internet is becoming the town square for the global village of tomorrow.” Bill Gates. The Internet is vast and is just getting bigger. It has its own community that is open to the public. The Internet is becoming a platform all on its own. It is a stepping-stone in a direction that is unknown. The Internet has become so vast that there are now different versions of it. The different versions of the web are Web 1.0, Web 2.0, the main focus of this paper, and Web 3.0. Web 1.0 is all about sharing information. It is very bland and just gets the point across of what was needed. This how the Internet had started. Web 2.0 is sharing information with interaction. To me this means social media in some fashion. The website that was accessed has a way of interacting with the users whether it be through comments or giveaways on the web. Web 3.0 is the server interacting with the individual on a particular website. Amazon is the best example of Web 3.0 because it gives recommendations based on items that have been searched. “Among American adults 87% use the web, 68% connect...
Deitel, P.J., and H. M. Deitel. Internet & World Wide Web How to Program: Fourth Edition.
Web 3.0 also means that if the user was to search for something such as ‘man’ it would not just display results just for ‘man’ it will also know to display ...
In the record of the web log server, clustering will be carry out to identify and group the information such as gender, name, phone number, e-mail address and so on into cluster. This will help the website to always keep contact with the users and know about their needs in order to exploit the website business market and also improve the web presence.