The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Estimation of Distribution Algorithms have proved to be very competitive for solving combinatorial and continuous optimisation problems. However, there are problems for which they have not been extensively developed: we refer to constrained optimisation problems. Existing proposals approach these problems by (i) modifying the sampling strategy of the probabilistic model to allow feasible solutions...
Mutation testing is widely considered as a high-end test criterion due to the vast number of mutants it generates. Although many efforts have been made to reduce the computational cost of mutation testing, its scalability issue remains in practice. In this paper, we introduce a novel method to speed up mutation testing based on state infection information. In addition to filtering out uninfected test...
A semi-lattice based activity model has been introduced to infer human daily activity within smart environment. For the purpose of improving the accuracy of activity recognition as well as to further study the layer function in lattice structure, we've explored the relationship between sensor and activity, and the relationship between different activities in this paper. Through the analysis of relations...
Nowadays Information Retrieval (IR) is difficult because of huge amount of information published on the Internet. So it is very relevant to organize documents based on its content. The proposed work address this issue by generating concepts from the documents and these documents are grouped based on a data mining approach. To generate the concept, keywords are extracted from the documents but the...
Borgs et al. [2016] investigated essential requirements for communities in preference networks. They defined six axioms on community functions, i.e., community detection rules. Though having elegant properties, the practicality of this axiomsystem is compromised by the intractability of checking twocritical axioms, so no nontrivial consistent community functionwas reported in [Borgs et al., 2016]...
Massive data applications such as E-science applications are characterized by complex treatments on large amounts of data which need to be stored in distributed data centers. In fact, when one task needs several datasets from different data centers, moving these data may cost a lot of time and cause energy's high consumption. Moreover, when the number of the data centers involved in the execution...
In this work, we propose a new framework called sequential reduction (SR) for reducing lattice bases, which harnesses the approximate closest vector problem (εCVP) oracles to sequentially reduce each basis vector. With the best εCVP oracle to serve as the theoretical upper limit of this scheme, our bound on basis lengths can be better than that of Minkowski's reduction under a mild assumption. A practical...
In scientific and technical software, floating-point arithmetic is often used to approximate arithmetic on physical quantities natively modeled as reals. Checking properties for such programs (e.g. proving unreachability of code fragments) requires accurate reasoning over floating-point arithmetic. Currently, most of the SMT-solvers addressing this problem class rely on bit-blasting. Recently, methods...
Criminal Intelligence Analysis often requires a search different from the semantic and keyword based searching to reveal the associations among semantically and operationally connected objects within a crime knowledge base. In this paper we introduce associative search as a search along the networks of association between objects like people, places, other organizations, products, events, services,...
Software product lines often use preprocessor statements as a basis for representing variability, which makes understanding the artifacts rather complex. An approach that has been proposed in the past to improve the understanding of code with preprocessor statements is formal concept analysis. This approach has been applied to a number of causes in reengineering. However, the lattices constructed...
Cascading style sheets (CSS) is a language that describes the presentation of web documents. CSS is widely adopted in web development and it is now common for web projects to have several thousands of CSS lines of code. Because the language lacks advanced features to allow code reuse, several languages such as Sass and Less have emerged as extensions to CSS. They provide mechanisms such as mixins...
This paper presents a candidate lattice refinement method for online handwritten Japanese text recognition. In the integrated segmentation-recognition framework, we first over-segment a character string pattern into primitive segments at least at their true boundaries so that each primitive segment may compose a single character or a part of a character. Then a candidate lattice is constructed based...
Expertise retrieval has already gained significant interest in the area of information retrieval due to multitude of concrete application contexts where search for specific experts is required. In this paper, we introduce a formal concept analysis approach for clustering of a group of experts with respect to given subject areas. Initially, the domain of interest is presented at some level of abstraction...
We present detailed analysis of phoneme recognition performance of a context dependent tied-state triphone Gaussian Mixture Model Hidden Markov Model (CD-GMM-HMM) acoustic model (state-of-the-art large acoustic model (AM)) and a four hidden layer context dependent Deep Neural Network (CD-DNN-HMM) AM on the WSJ speech corpus. Using a bigram phoneme language model, phoneme recognition experiments are...
In the paper we give a characterization of identifiability for regularizations with gauges of compact convexes. This extends the classic identifiability results from the standard l1-regularization framework in compressive sensing. We show that the standard dual certificate techniques can no longer work by themselves ouside the polytope case. We then apply the general characterization to the caseof...
Stored data in database can hide some knowledge, which is interesting, useful to hidden knowledge discover. In this context, an algorithms number a frequent itemsets and association rules extraction were presented. Special feature of these algorithms is to generation a large number of rules, making their exploitation a difficult task. In this paper we will introduce a new algorithm for association...
As the size of data table grows, the concepts generated become larger in number. Making sure the set of extent remaining unchanged, the purpose of attribute reduction of concept lattice is to find out minimum subsets of attributes and make knowledge presented by concept lattice simpler, decision problem simplified as well. This paper introduced the definition of introducer which was minimum closure...
We present a novel strategy for tracking time-dependant waves. The theory is structured upon a discrete phase-space set of pulsed beam (PB) waves (space-time wavepackets), which is shown to constitute an overcomplete frame. We show that the field radiated by any time-dependent volume source distribution (with aperture sources being a special case) can be expanded as a sum of these PB wavefields. The...
In this short paper, we describe a conceptual approach in which Conceptual Graphs (CGs) and Formal Concept Analysis (FCA) are employed towards knowledge discovery in online drug transactions. The transactions are acquired by performing Named-Entity Recognition (NER) on documents crawled from online public sources such as Twitter and Instagram, and are structured based on a CG ontology created to model...
Classification rule mining is one of important areas of data mining, and it is a hot subject at present. In this paper, we introduce some definitions: relevant concept, pseudo concept, and relevant concept cover. Then we presents an algorithm to compute relevant concept cover, which divides the context into subsets, calculate the set of relevant concepts by the value of concept shannon entropy, and...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.