WEBOMETRICS RESEARCH METHODS ADOPTED IN LIBRARY AND INFORMATION SCIENCE: AN OVERVIEW

Abstract At the moment, the technologies and applications have made the internet an important medium of communication and information dissemination. It provides a much enhanced interface between the user and information. The web set the foundation for global communication of computer users. Increasing the importance of web is clearly seen in the form of references or citations in the present day publications. Studies of the Web have been named webometrics or cybermetrics as in the electronic journal of that name. The web in particular has made all kinds of information easier to access and has encouraged people to make information publically available that they previously would not have thought to do. It was a huge advantage for researchers and students because the information needed to study a phenomenon might be freely available online, saving time in the data collection phase of a project and making larger scale studies possible.webometrics research is having some impact in other disciplines in the sense of attracting citations. These include the cognate disciplines of computer science, Sociology, Physics and Complex science. For some years bibliometric studies have identified webometrics as one of the largest information science fields. Nevertheless, most published webometrics research is relatively theoretical and, as a new research field, seems unlikely to survive unless it is useful in some way. In general it is very important for academics to identify hot research topics and avoid unpromising ones and so methods are needed to help this identification process. Moreover, there is a significant amount of citation of webometrics research by disciplines outside information science, including computing, sociology, physics and complex science. Nevertheless, it seems that the potential user base for current webometric techniques is wider still, creating a need for awareness-raising

WEBOMETRICS RESEARCH METHODS ADOPTED IN LIBRARY AND INFORMATION SCIENCE: AN OVERVIEW

Abstract At the moment, the technologies and applications have made the internet an important medium of communication and information dissemination. It provides a much enhanced interface between the user and information. The web set the foundation for global communication of computer users. Increasing the importance of web is clearly seen in the form of references or citations in the present day publications. Studies of the Web have been named webometrics or cybermetrics as in the electronic journal of that name. The web in particular has made all kinds of information easier to access and has encouraged people to make information publically available that they previously would not have thought to do. It was a huge advantage for researchers and students because the information needed to study a phenomenon might be freely available online, saving time in the data collection phase of a project and making larger scale studies possible.webometrics research is having some impact in other disciplines in the sense of attracting citations. These include the cognate disciplines of computer science, Sociology, Physics and Complex science. For some years bibliometric studies have identified webometrics as one of the largest information science fields. Nevertheless, most published webometrics research is relatively theoretical and, as a new research field, seems unlikely to survive unless it is useful in some way. In general it is very important for academics to identify hot research topics and avoid unpromising ones and so methods are needed to help this identification process. Moreover, there is a significant amount of citation of webometrics research by disciplines outside information science, including computing, sociology, physics and complex science. Nevertheless, it seems that the potential user base for current webometric techniques is wider still, creating a need for awareness-raising

The Best Answers? Think Twice: Online Detection of Commercial Campaigns in the CQA Forums

In an emerging trend, more and more Internet users search for information from Community Question and Answer (CQA) websites, as interactive communication in such websites provides users with a rare feeling of trust. More often than not, end users look for instant help when they browse the CQA websites for the best answers. Hence, it is imperative that they should be warned of any potential commercial campaigns hidden behind the answers. However, existing research focuses more on the quality of answers and does not meet the above need. In this paper, we develop a system that automatically analyzes the hidden patterns of commercial spam and raises alarms instantaneously to end users whenever a potential commercial campaign is detected. Our detection method integrates semantic analysis and posters' track records and utilizes the special features of CQA websites largely different from those in other types of forums such as microblogs or news reports. Our system is adaptive and accommodates new evidence uncovered by the detection algorithms over time. Validated with real-world trace data from a popular Chinese CQA website over a period of three months, our system shows great potential towards adaptive online detection of CQA spams.Comment: 9 pages, 10 figure

Review Paper on Answers Selection and Recommendation in Community Question Answers System

Nowadays, question answering system is more convenient for the users, users ask question online and then they will get the answer of that question, but as browsing is primary need for each an individual, the number of users ask question and system will provide answer but the computation time increased as well as waiting time increased and same type of questions are asked by different users, system need to give same answers repeatedly to different users. To avoid this we propose PLANE technique which may quantitatively rank answer candidates from the relevant question pool. If users ask any question, then system provide answers in ranking form, then system recommend highest rank answer to the user. We proposing expert recommendation system, an expert will provide answer of the question which is asked by the user and we also implement sentence level clustering technique in which a single question have multiple answers, system provide most suitable answer to the question which is asked by the user

From Amateurs to Connoisseurs: Modeling the Evolution of User Expertise through Online Reviews

Recommending products to consumers means not only understanding their tastes, but also understanding their level of experience. For example, it would be a mistake to recommend the iconic film Seven Samurai simply because a user enjoys other action movies; rather, we might conclude that they will eventually enjoy it -- once they are ready. The same is true for beers, wines, gourmet foods -- or any products where users have acquired tastes: the `best' products may not be the most `accessible'. Thus our goal in this paper is to recommend products that a user will enjoy now, while acknowledging that their tastes may have changed over time, and may change again in the future. We model how tastes change due to the very act of consuming more products -- in other words, as users become more experienced. We develop a latent factor recommendation system that explicitly accounts for each user's level of experience. We find that such a model not only leads to better recommendations, but also allows us to study the role of user experience and expertise on a novel dataset of fifteen million beer, wine, food, and movie reviews.Comment: 11 pages, 7 figure