Data Mining - Concepts and Techniques.

Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things. This article provides an overview of recommender systems as well as collaborative filtering methods and algorithms; it also explains their evolution, provides an original classification for these systems, identifies areas of future implementation and develops certain areas selected for past, present or future importance.

http://romisatriawahono.net/lecture/rm/survey/information%20retrieval/Bobadilla%20-%20Recommender%20Systems%20-%202013.pdf

Recommender systems survey

Matrix Factorization Techniques for Recommender Systems

The problem of which cues, internal or external, permit a person to label and identify his own emotional state has been with us since the days that James (1890) first tendered his doctrine that \"the bodily changes follow directly the perception of the exciting fact, and that our feeling of the same changes as they occur is the emotion\" (p. 449). Since we are aware of a variety of feeling and emotion states, it should follow from James' proposition that the various emotions will be accompanied by a variety of differentiable bodily states. Following James' pronouncement, a formidable number of studies were undertaken in search of the physiological differentiators of the emotions. The results, in these early days, were almost uniformly negative. All of the emotional states experi-

"Cognitive, social, and physiological determinants of emotional state": Erratum

/pdf/qualitative-research-in-information-systems-1sezxwy02d.pdf

Qualitative Research in Information Systems

The sorting nexin (SNX) protein family is implicated in regulating membrane traffic, but the mechanism is still unknown. We show that SNX3 is associated with the early endosome through a novel motif (PX domain) capable of interaction with phosphatidylinositol-3-phosphate (PtdIns(3)P). Overexpression of SNX3 alters endosomal morphology and delays transport to the lysosome. Transport from the early to the recycling endosome is affected upon microinjection of SNX3 antibodies. Our results highlight a novel mechanism by which SNX proteins regulate traffic and uncover a novel class of effectors for PtdIns(3)P.

SNX3 regulates endosomal function through its PX-domain-mediated interaction with PtdIns(3)P.

Prenylation-dependent association of protein-tyrosine phosphatases PRL-1, -2, and -3 with the plasma membrane and the early endosome.

With the explosion of Web 2.0 application such as blogs, social and professional networks, and various other types of social media, the rich online information and various new sources of knowledge flood users and hence pose a great challenge in terms of information overload. It is critical to use intelligent agent software systems to assist users in finding the right information from an abundance of Web data. Recommender systems can help users deal with information overload problem efficiently by suggesting items (e.g., information and products) that match users' personal interests. The recommender technology has been successfully employed in many applications such as recommending films, music, books, etc. The purpose of this report is to give an overview of existing technologies for building personalized recommender systems in social networking environment, to propose a research direction for addressing user profiling and cold start problems by exploiting user-generated content newly available in Web 2.0.

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The state-of-the-art in personalized recommender systems for social networking

Text mining is the technique that helps users find useful information from a large amount of digital text documents on the Web or databases. Instead of the keyword-based approach which is typically used in this field, the pattern-based model containing frequent sequential patterns is employed to perform the same concept of tasks. However, how to effectively use these discovered patterns is still a big challenge. In this study, we propose two approaches based on the use of pattern deploying strategies. The performance of the pattern deploying algorithms for text mining is investigated on the Reuters dataset RCV1 and the results show that the effectiveness is improved by using our proposed pattern refinement approaches.

/pdf/deploying-approaches-for-pattern-refinement-in-text-mining-lvo8qpebr7.pdf

Deploying Approaches for Pattern Refinement in Text Mining

In this paper, we propose a model for discovering frequent sequential patterns, phrases, which can be used as profile descriptors of documents. It is indubitable that we can obtain numerous phrases using data mining algorithms. However, it is difficult to use these phrases effectively for answering what users want. Therefore, we present a pattern taxonomy extraction model which performs the task of extracting descriptive frequent sequential patterns by pruning the meaningless ones. The model then is extended and tested by applying it to the information filtering system. The results of the experiment show that pattern-based methods outperform the keyword-based methods. The results also indicate that removal of meaningless patterns not only reduces the cost of computation but also improves the effectiveness of the system.

/pdf/automatic-pattern-taxonomy-extraction-for-web-mining-r2ry7kqy0q.pdf

Yue Xu

Papers

SNX3 regulates endosomal function through its PX-domain-mediated interaction with PtdIns(3)P.

Prenylation-dependent association of protein-tyrosine phosphatases PRL-1, -2, and -3 with the plasma membrane and the early endosome.

The state-of-the-art in personalized recommender systems for social networking

Deploying Approaches for Pattern Refinement in Text Mining

Automatic Pattern-Taxonomy Extraction for Web Mining