Data mining is sorting through data to identify patterns and establish relationships. Association rule mining is a well established method of data mining that identifies significant correlations between items in transactional data. Measures like support count, comprehensibility and interestingness, used for evaluating a rule can be thought of as different objectives of association rule mining p...

journal of accounting advances (j.a.a) vol. 5, no. 1, 2013, ser. 64/3     extended abstract   an analysis of the effects of growth opportunities on financial leverage of companies listed on tehran stock exchange   dr. s. samadi                  s. soheili                   v. kabiripour isfahan university   introduction the ability of companies in identifying the potential financial sources to ...

Information opacity leads to information asymmetry. In this situation, in providing their own financial needs, firms face limitations and inevitably provide their financial needs from the debt market by signalling private information to it. In addition, information opacity affects the leverage adjustment speed. This research investigates the effect of information opacity on deviation from targe...

This data article provides detailed optimization input and output datasets and optimization code for the published research work titled "Dynamic green supplier selection and order allocation with quantity discounts and varying supplier availability" (Hamdan and Cheaitou, 2017, In press) [1]. Researchers may use these datasets as a baseline for future comparison and extensive analysis of the gre...

Collaborative Filtering (CF) is a widely used technique in recommendation systems to suggest items users based on their previous interactions with the system. CF involves finding correlations between preferences of different and using those provide recommendations. This can be divided into user-based item-based CF, both which utilize similarity metrics generate Content-based filtering another c...

Matrix Factorization based Collaborative Filtering (MFCF) has been an efficient method for recommendation. However, recent years have witness the explosive increasing of big data, which contributes to the huge size of users and items in recommender systems. To deal with the efficiency of MFCF recommendation in the context of big data challenge, we propose to leverage MapReduce programming model...

One key component of creating an intelligent tutoring system is forming a model that monitors student behavior. Researchers in machine learning area have been using automatic/semi-automatic techniques to search for cognitive models. One of the semi-automatic approaches is learning factor analysis, which involves human making hypothesis and identifying difficulty factors in the related items. In...

T sale of digital items, such as avatars and decorative objects, is becoming an important source of revenue for virtual community (VC) websites. However, some websites are unable to leverage this source of revenue, and there is a corresponding lack of understanding about what motivates people to purchase digital items in VCs. To explain the phenomenon, we develop a model based on the theory of ...