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.
This paper contains analysis and extension of exploiters-based knowledge extraction methods, which allow generation of new knowledge, based on the basic ones. The main achievement of the paper is useful features of some universal exploiters proof, which allow extending set of basic classes and set of basic relations by finite set of new classes of objects and relations among them, which allow creating...
There are some independent cyber security knowledge bases for different aspect now. In the internet, there is also much cyber security related content which exists in the form of text. Fusion of these cyber security related information can be a meaningful work. In this paper, we propose a framework to integrate existing cyber security knowledge base and extract cyber security related information from...
It is critical to detect and correct information errors effectively to achieve higher data quality in many applications. Most existing techniques only use the intrinsic information to detect and correct a database, provided that data is adequate and well-structured. These techniques will not work properly if there is no sufficient data available. Integrating the information from external sources,...
Highly expressive declarative languages, such as Datalog, are now commonly used to model the operational logic of data-intensive applications. The typical complexity of such Datalog programs, and the large volume of data that they process, call for the tracking and presentation of data provenance. Provenance information is crucial for explaining and justifying the Datalog program results. However,...
This research aims to automate the process of gathering online, end user reviews for any given product or service and analyzing those reviews in terms of the sentiments expressed about specific features. This involves the filtering of irrelevant and unhelpful reviews, quantification of the sentiments of thousands of (useful) reviews. And finally, providing the end user (business/manufacturer) summarized...
Innumerable terror and suspicious messages are sent through Instant Messengers (IM) and Social Networking Sites (SNS) which are untraced, leading to hindrance for network communications and cyber security. We propose a Framework that discover and predict such messages that are sent using IM or SNS like Facebook, Twitter, LinkedIn, and others. Further, these instant messages are put under surveillance...
Cognitive radio (CR) is viewed as a promising technology that can bring about remarkable improvement in spectrum utilization. Different cognition cycles have been proposed to direct basic research areas in CR. However, most of the existing studies only emphasize on its functional or operational aspects regardless of the intelligent core, the essential aspect, and the external aspect of cognition cycle...
Statistical data is one of the most important sources of information, relevant for large numbers of stakeholders in the governmental, scientific and business domains alike. In this article, we overview how statistical data can be managed on the Web. With OLAP2 Data Cube and CSV2 Data Cube we present two complementary approaches on how to extract and publish statistical data. We also discuss the linking,...
Human commonsense is required to improve quality of robotic application. However, to acquire the necessary knowledge, robot needs to evaluate the appropriateness of the data it has collected. This paper presents an evaluation method, by combining the weighting mechanism in commonsense databases with a set of weighting factors. The method was verified on our Basic-level Knowledge Network. We conducted...
A host of tools and techniques are now available for data mining on the Internet. The explosion in social media usage and people reporting brings a new range of problems related to trust and credibility. Traditional media monitoring systems have now reached such sophistication that real time situation monitoring is possible. The challenge though is deciding what reports to believe, how to index them...
Businesses are increasingly realizing the value of creating a {\it single view} of its customers and partners by integrating information residing in 'siloed' datasets within and outside the enterprise. However, the task of {\it augmenting} data available within the enterprise with data purchased from third-party providers or that residing in a public domain such as Web often results in warehouses...
Living in the modern technology dependent world, we heavily rely on electronically stored data and information, to come up with sound and timely decisions. Considering the entire information technology world, there exists an unimaginable volume of data which contains a lot of information which is relevant to various kinds of fields. But the problem emerges when we are interested to find out about...
With the development of research and application of data mining and knowledge acquisition, the requirements for accessing to state, variation and causality contained in scientific and engineering data set have been increasing. In this paper, for analyzing and mining the continuous and time-varying data, an algorithm for state data mining is proposed, which is based on language value structure and...
In this paper, we put forward our approach for answering aggregated queries over imprecise data using domain specific taxonomies. A new concept we call the weighted hierarchical hyper graph has been introduced, which helps in answering aggregated queries when dealing with imprecise databases. We assume that the existence of a knowledge base is permanent and independent of the imprecision in the database...
This paper introduces a rule-based Attribute-Oriented (AO) Induction method on rule-based concept hierarchies that can be constructed from generalization rules. Based on analyzing some major previous approaches such as rule-based AO induction with backtracking, path-id based AO induction and a cyclic graph based AO induction, we propose a new approach to facilitate induction on the rule based case...
The knowledge discovery of driver behavior in traffic accident database is implemented based on multi-agent technology. The multi-agent technology helps to solve the complexity problems of both discovery and driver's behavior, and achieve more intelligence for driver behavior knowledge discovery. The application of pair-database-coordination mechanism and heuristic algorithm makes the knowledge discovery...
Causality is not only a matter of causal statements, but also of conditional sentences. In conditional statements, causality generally emerges from the entailment relationship between the antecedent and the consequence. This entailment is frequently vague and uncertain in nature. In this article, we present a method of retrieving crisp and imperfect conditional and causal sentences identified by some...
Linguistic summarization (LS) is a data mining or knowledge discovery approach to extract patterns from databases. It has been studied by many researchers; however, none of them has used it to generate IF-THEN rules, which can be added to a knowledge base for better understanding of the data, or be used in Perceptual Reasoning to infer the outputs for new scenarios. In this paper LS using IF-THEN...
This study presents a new comprehensive framework for semantic content extraction from raw video, storage of the extracted data and retrieval of the stored data. Objects, spatial relations between objects, events and temporal relations between events, which are considered as semantic contents of the video, are extracted automatically to a certain extend with the developed approach. Extraction process...
Data warehouse course is a discipline that includes many subjects. There are theoretical teaching and practical teaching in this course. This paper introduces a new teaching method that is called an embedded teaching method. This method is applied to the data warehouse course successfully. Firstly, the ideas of this method are presented. Some associative knowledge in other courses is integrated to...
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.