Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework

Krajča, Petr; Vychodil, Vilém

doi:10.1007/978-3-642-03915-7_29

Cited by 34 publications

(17 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Krajca et al [14], [15] have proposed algorithms which allow us to perform closed pattern mining simultaneously either in parallel or in a distributed manner. Their approaches are orthogonal to ours; it would be beneficial to employ their algorithms for computing local closed patterns in the mining phase in our framework.…”

Section: Discussionmentioning

confidence: 99%

Towards efficient closed pattern mining from distributed multi-relational data

Kamiya

Seki

2014

2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Ad

View full text Add to dashboard Cite

We consider closed pattern mining from distributed multi-relational databases, especially focusing on its efficient implementation. Given a set of local databases (horizontal partitions), we first compute their sets of closed patterns (concepts) using a closed pattern mining algorithm tailored to multirelational data mining (MRDM). We then generate the set of closed patterns in the global database by utilizing the merge (or subposition) operator, studied in the field of Formal Concept Analysis. Since the computational complexity of MRDM increases compared with the conventional itemset mining, we propose some methods for improving the overall computations. We also present some experimental results using a distributed computation environment based on the MapReduce framework, which shows the effectiveness of the proposed methods.

show abstract

Section: Discussionmentioning

confidence: 99%

Towards efficient closed pattern mining from distributed multi-relational data

Kamiya

Seki

2014

2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Ad

View full text Add to dashboard Cite

show abstract

“…It was mostly aimed to support scientific and teaching activities in the field of Machine Learning and Data Mining. However, since QuDA has open architecture and support the most common data formats as well as the Predictive Model Markup Language (PMML) 22 , it can be easily integrated into a working Data Mining circle. Originally, it was an acronym for "Qualitative Data Analysis".…”

Section: Machine Learning Exercises With Jsm-methods In Qudamentioning

confidence: 99%

“…Process(Z, f, (X, Y )) 9: end for One can note that the traverse of the generation tree is done in a depth-first search manner. After the inception of the first batch algorithms, the broadened FCA inventory includes efficient incremental algorithms [21] and the distributed versions of NextClosure and CbO for MapReduce [22,23].…”

Section: Algorithm 2 Close By Onementioning

confidence: 99%

Introduction to Formal Concept Analysis and Its Applications in Information Retrieval and Related Fields

Ignatov

2015

Communications in Computer and Information Science

View full text Add to dashboard Cite

Abstract. This paper is a tutorial on Formal Concept Analysis (FCA) and its applications. FCA is an applied branch of Lattice Theory, a mathematical discipline which enables formalisation of concepts as basic units of human thinking and analysing data in the object-attribute form. Originated in early 80s, during the last three decades, it became a popular human-centred tool for knowledge representation and data analysis with numerous applications. Since the tutorial was specially prepared for RuS-SIR 2014, the covered FCA topics include Information Retrieval with a focus on visualisation aspects, Machine Learning, Data Mining and Knowledge Discovery, Text Mining and several others.

show abstract

“…The main task of AZS is reasoning to decide a set of user/group according to constraints and computed relations in the query. Because our design is based on a cloud environment, we can take advantage of some powerful distributed computing algorithms to improve system response time [8]. …”

Section: The Model Of Ca-abacmentioning

confidence: 99%

CA-ABAC: Class Algebra Attribute-Based Access Control

Buehrer

Wang

2012

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology

View full text Add to dashboard Cite

We propose a trust framework model for an educational cloud which is designed to overcome inequalities of M-shaped incomes by simplifying contract-based sharing of resources among multiple schools. We use class algebra, which is similar to SROIQ(D) description logic, as the access control policy language. Benefiting from the high expressivity of class algebra, our model can use implicit relations and reasoning to enforce access control that corresponds to the contracts. The security mechanism allows one-time user login to obtain all of this user's credentials for accessing services. In addition, our model can select appropriate material to adapt to the level of the student by adding the classification information to the attributes of the educational material and the student, and integrating this information into the access control policy to build an exclusive learning graph for each student.

show abstract

Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework

Cited by 34 publications

References 12 publications

Towards efficient closed pattern mining from distributed multi-relational data

Towards efficient closed pattern mining from distributed multi-relational data

Introduction to Formal Concept Analysis and Its Applications in Information Retrieval and Related Fields

CA-ABAC: Class Algebra Attribute-Based Access Control

Contact Info

Product

Resources

About