Using data from web-server logs to develop a concept-based browse set for water quality and agriculture

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Discovery Is Never By Chance: Designing for (Un)Serendipity

Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by ‘association-hunting’ agents. We propose considering not only the inventor’s role in perceiving serendipity, but also how that inventor’s perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately

Rule-based User Characteristics Acquisition from Logs with Semantics for Personalized Web-Based Systems

Personalization of web-based information systems based on specialized user models has become more important in order to preserve the effectiveness of their use as the amount of available content increases. We describe a user modeling approach based on automated acquisition of user behaviour and its successive rule-based evaluation and transformation into an ontological user model. We stress reusability and flexibility by introducing a novel approach to logging, which preserves the semantics of logged events. The successive analysis is driven by specialized rules, which map usage patterns to knowledge about users, stored in an ontology-based user model. We evaluate our approach via a case study using an enhanced faceted browser, which provides personalized navigation support and recommendation

Publishing Primary Data on the World Wide Web: Opencontext.org and an Open Future for the Past

More scholars are exploring forms of digital dissemination, including open access (OA) systems where content is made available free of charge. These include peer -reviewed e -journals as well as traditional journals that have an online presence. Besides SHA's Technical Briefs in Historical Archaeology, the American Journal of Archaeology now offers open access to downloadable articles from their printed issues. Similarly, Evolutionary Anthropology offers many full -text articles free for download. More archaeologists are also taking advantage of easy Web publication to post copies of their publications on personal websites. Roughly 15% of all scholars participate in such "self -archiving." To encourage this practice, Science Commons (2006) and the Scholarly Publishing and Academic Resources Coalition (SPARC) recently launched the Scholar Copyright Project, an initiative that will develop standard "Author Addenda" -- a suite of short amendments to attach to copyright agreements from publishers (http://sciencecommons. org/projects/publishing/index.html). These addenda make it easier for paper authors to retain and clarify their rights to self -archive their papers electronically. Several studies now clearly document that self -archiving and OA publication enhances uptake and citation rates (Hajjem et al. 2005). Researchers enhance their reputations and stature by opening up their scholarship.Mounting pressure for greater public access also comes from many research stakeholders. Granting foundations interested in maximizing the return on their investment in basic research are often encouraging and sometimes even requiring some form of OA electronic dissemination. Interest in maximizing public access to publicly financed research is catching on in Congress. A new bipartisan bill, the Federal Research Public Access Act, would require OA for drafts of papers that pass peer review and result from federally funded research (U.S. Congress 2006). The bill would create government -funded digital repositories that would host and maintain these draft papers. University libraries are some of the most vocal advocates for OA research. Current publishing frameworks have seen dramatically escalated costs, sometimes four times higher than the general rate of inflation (Create Change 2003). Increasing costs have forced many libraries to cancel subscriptions and thereby hurt access and scholarship (Association for College and Research Libraries 2003; Suber 2004).This article originally published in Technical Briefs In Historical Archaeology, 2007, 2: -11

You, the Web and Your Device: Longitudinal Characterization of Browsing Habits

Understanding how people interact with the web is key for a variety of applications, e.g., from the design of effective web pages to the definition of successful online marketing campaigns. Browsing behavior has been traditionally represented and studied by means of clickstreams, i.e., graphs whose vertices are web pages, and edges are the paths followed by users. Obtaining large and representative data to extract clickstreams is however challenging. The evolution of the web questions whether browsing behavior is changing and, by consequence, whether properties of clickstreams are changing. This paper presents a longitudinal study of clickstreams in from 2013 to 2016. We evaluate an anonymized dataset of HTTP traces captured in a large ISP, where thousands of households are connected. We first propose a methodology to identify actual URLs requested by users from the massive set of requests automatically fired by browsers when rendering web pages. Then, we characterize web usage patterns and clickstreams, taking into account both the temporal evolution and the impact of the device used to explore the web. Our analyses precisely quantify various aspects of clickstreams and uncover interesting patterns, such as the typical short paths followed by people while navigating the web, the fast increasing trend in browsing from mobile devices and the different roles of search engines and social networks in promoting content. Finally, we contribute a dataset of anonymized clickstreams to the community to foster new studies (anonymized clickstreams are available to the public at http://bigdata.polito.it/clickstream).Comment: 30 page

A Survey on Web Usage Mining

Now a day World Wide Web become very popular and interactive for transferring of information. The web is huge, diverse and active and thus increases the scalability, multimedia data and temporal matters. The growth of the web has outcome in a huge amount of information that is now freely offered for user access. The several kinds of data have to be handled and organized in a manner that they can be accessed by several users effectively and efficiently. So the usage of data mining methods and knowledge discovery on the web is now on the spotlight of a boosting number of researchers. Web usage mining is a kind of data mining method that can be useful in recommending the web usage patterns with the help of users2019; session and behavior. Web usage mining includes three process, namely, preprocessing, pattern discovery and pattern analysis. There are different techniques already exists for web usage mining. Those existing techniques have their own advantages and disadvantages. This paper presents a survey on some of the existing web usage mining techniques

Design and Implementation of a Web Usage Mining Model Based On Upgrowth and Preflxspan

Web Usage Mining (WUM) integrates the techniques of two popular research fields - Data Mining and the Internet. By analyzing the potential rules hidden in web logs, WUM helps personalize the delivery of web content and improve web design, customer satisfaction and user navigation through pre-fetching and caching. This paper introduces two prevalent data mining algorithms - FPgrowth and PrefixSpan into WUM and they are applied in a real business case. Maximum Forward Path (MFP) is also used in the web usage mining model during sequential pattern mining along with PrefixSpan so as to reduce the interference of false visit caused by browser cache and raise the accuracy of mining frequent traversal paths. Detailed analysis and application on the corresponding results are discussed

Optimized Model of Recommendation System for E-Commerce Website

The purpose of this work is to optimize the recommendation system by creating a new model of recommender system with different services in a global e-commerce website. In this model the most effective data sources are integrated to increase the accuracy of recommendations system, which provides the client more intuitive browsing categories interface. The sources used for this model are the user2019;s searching log on the global website, and data referred extracted from search engines, more clicked URLs, highly rated items, and the recommendation algorithms of new users and new items. In additions, user2019;s interests based on locations, and the hot releases items recommended by the admin or shop owner of the e-commerce website according to the website marketing strategy. When the users browse the website, the data sources will automatically combine to incorporate the derived structure and associate items for each category into a new browsing recommendation interface. The advantages of this model will assist the users to discover their real interested items with flexibility and high efficiency; it also provides some solutions for some serious problems and challenges that exist in the current recommendation services. Data mining technology and clustering algorithms have been proposed and applied to perform the idea of this work. ASP.NET is the implementation tool for the application website, Microsoft SQL server is used for database management