A Paper Recommendation System Dah Ming chiu December 17. 2008 Part of research is reading other people's publications-papers. This activity can take a tremen- dous amount of time, considering the rate at which papers are produced. Therefore a good re- searcher must selectively read papers There are many ways to select papers to read. Students seek advice from their supervisors Professors may be able to judge a paper's worthiness more quickly, from experience, from reputation of the authors, or from other community services such as peer review activities. Conferences and journals help select the fittest papers for their topic areas, at different stages of a piece of research work. Word-of-mouth also help propagate the knowledge of good papers. These mechanisms all help the process of research Once we scale up the community, the effectiveness of the above mechanisms quickly diminish From a personal perspective(as a researcher in computer networking), I am publishing in a dozen or more conferences/journals, seeing conference, workshop and other publication venues at an estimated rate of a hundred per year. Some conferences are rather large; for example IEEE Infocom publishes 200+ papers each year. The scale has reached a point that I cannot keep up with even keeping track of those papers that directly relate to my research Since all the researchers in the community should be in the same shoes, why not create a mechanism to collectively solve this problem? The idea is to build a paper recommendation system Each(experienced) researcher recommends a paper based on the subset of papers visible to him/her ideally, the recommendation comes with a digest of what the paper is about and the reasons why it is recommended To ensure these recommendations are useful, they should satisfy the following properties 1. Quality-They should come from experts who have read the paper carefully 2. Accessibility- They should be categorized appropriately for easy access. For example, each user should be able to customize his/her own view of recommended papers of interest to him 3. Ranking -They should be ranked. The recommendations will have different quality, freshness and relevance. Like the results returned by a search engine, the ranking of recommendation is very important The following are major challenges in building such a systme Business model- This is not necessarily related to making a business out of this service. Rather, it is about how to have an incentive system so that the system can self-sustain; namely how to make sure good recommendations keep deally, it can self-sustain as a sizable social network. Contributors contribute mainly because of social reasons: for example, they become thought-leaders, or they get satisfaction from helping others or contributing to a good cause. Another possibility, which I believe is necessary, is to provide some form of financial This can happen for a variety of reasons, such as research funding increase, or internalization of researchA Paper Recommendation System Dah Ming Chiu December 17, 2008 Part of research is reading other people’s publications - papers. This activity can take a tremen￾dous amount of time, considering the rate at which papers are produced. Therefore a good re￾searcher must selectively read papers. There are many ways to select papers to read. Students seek advice from their supervisors. Professors may be able to judge a paper’s worthiness more quickly, from experience, from reputation of the authors, or from other community services such as peer review activities. Conferences and journals help select the fittest papers for their topic areas, at different stages of a piece of research work. Word-of-mouth also help propagate the knowledge of good papers. These mechanisms all help the process of research. Once we scale up the community1, the effectiveness of the above mechanisms quickly diminish. From a personal perspective (as a researcher in computer networking), I am publishing in a dozen or more conferences/journals, seeing conference, workshop and other publication venues at an estimated rate of a hundred per year. Some conferences are rather large; for example IEEE Infocom publishes 200+ papers each year. The scale has reached a point that I cannot keep up with even keeping track of those papers that directly relate to my research. Since all the researchers in the community should be in the same shoes, why not create a mechanism to collectively solve this problem? The idea is to build a paper recommendation system. Each (experienced) researcher recommends a paper based on the subset of papers visible to him/her. Ideally, the recommendation comes with a digest of what the paper is about and the reasons why it is recommended. To ensure these recommendations are useful, they should satisfy the following properties: 1. Quality - They should come from experts who have read the paper carefully. 2. Accessibility - They should be categorized appropriately for easy access. For example, each user should be able to customize his/her own view of recommended papers of interest to him/her. 3. Ranking - They should be ranked. The recommendations will have different quality, freshness, and relevance. Like the results returned by a search engine, the ranking of recommendations is very important. The following are major challenges in building such a systme: 1. Business model - This is not necessarily related to making a business out of this service. Rather, it is about how to have an incentive system so that the system can self-sustain; namely how to make sure good recommendations keep coming. Ideally, it can self-sustain as a sizable social network. Contributors contribute mainly because of social reasons: for example, they become thought-leaders, or they get satisfaction from helping others or contributing to a good cause. Another possibility, which I believe is necessary, is to provide some form of financial 1This can happen for a variety of reasons, such as research funding increase, or internalization of research com￾munities. 1