Collaborative Filtering of Call for Papers

Abstract

Call for papers (CFPs) are notifications of academic events that invite researchers to submit their works. Traditionally, CFPs are handed out to researchers by mailing lists and web pages. With the number of conferences increasing, finding, reading and filtering out relevant CFPs become time consuming and need the assistance from information retrieval techniques. In this paper, we employ collaborative filtering to match relevant CFPs to researchers. Non-personalized, neighborhood-based and class-based methods are applied in CFP recommendation. We also propose a hybrid approach that utilizes conference series and submission deadlines of CFPs. The experiments on WikiCFP data set show that the class-based method outperforms both neighborhood-based and non-personalized methods, whereas the proposed hybrid approach has the best overall performance.

OpenResearch: Collaborative Management of Scholarly Communication Metadata

“…Xia et al presented a classification method to filter CfPs by social tagging [10]. Wang et al proposed another approach to classify CfPs by implementing three different methods but focus on comparing the classification methods rather than services to improve scientific communication [9].…”

“…GSM's ranking method only considers the number of citations, whereas we intend to offer a multi-disciplinary service with a flexible search mechanism based on several quality metrics. DBLP 9 , one of the most widely known bibliographic databases in computer science, provides information mainly about publications but also considers related entities such as authors, editors, conference proceedings and journals. Events, deadlines and subjects are out of DBLP's scope.…”

Towards a Cloud-Based Service for Maintaining and Analyzing Data About Scientific Events

“…Xia et al presented a classification method to filter CfPs by social tagging [10]. Wang et al proposed another approach to classify CfPs by implementing three different methods but focus on comparing the classification methods rather than services to improve scientific communication [9]. Paperleap 5 is a commercial tool for analyzing CfPs and provide recommendations for users.…”