Similarity increases collaborative cheating
نویسندگان
چکیده
منابع مشابه
Cheating or ‘Collaborative Work’: Does it Pay?
Being a distance education institution, our current infrastructure does not allow group or collaborative work on undergraduate level. Although students are allowed to work together and assist each other, each student is required to submit individual attempts for assignments and/or projects. Assignments that are so similar that we could not accept them as individual attempts are considered cheat...
متن کاملan optimal similarity measure for collaborative filtering using firefly algorithm
recommender systems (rs) provide personalized recommendation according to user need by analyzing behavior of users and gathering their information. one of the algorithms used in recommender systems is user-based collaborative filtering (cf) method. the idea is that if users have similar preferences in the past, they will probably have similar preferences in the future. the important part of col...
متن کاملCheating Cheating Detectors
In this paper we present a new cheating technique that is successful at defeating cheating detectors and could become popular with students. The idea is to use obfuscating code transformations (such as those found in the SANDMARK tool) to apply a sequence of minor code transformations to a copied programming assignment. This purpose is to produce a copy that will defeat detection. We show that ...
متن کاملA New Similarity Measure Based on Item Proximity and Closeness for Collaborative Filtering Recommendation
Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...
متن کاملA NOVEL FUZZY-BASED SIMILARITY MEASURE FOR COLLABORATIVE FILTERING TO ALLEVIATE THE SPARSITY PROBLEM
Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Economic Behavior & Organization
سال: 2020
ISSN: 0167-2681
DOI: 10.1016/j.jebo.2020.06.022