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Recently α-cut irreducible and δ1δ2-multi-adjoint concept lattices have been introduced as two different methodologies focus on reducing the size of a given fuzzy concept lattice. The philosophy of both methodologies is completely different and so, the obtained lattices too. This paper analyzes the differences and proposes that the best is to combine both methodologies in order to obtain new procedures...
The rise of internet web-based application and smart phone ease access to the stock market, attracting newcomer investors. Most investors have made their decision based on information from stock investment researches published by the brokers. An automated stock recommendation system from stock investment research is introduced in this paper. The system collects several investment researches from multiple...
Public repositories for gene expression studies have been growing rapidly in the last decade. Retrieval of gene expression experiments based on textual descriptions does not provide sufficient data for biologists and clinicians. Content-based search has recently become more desirable in retrieving similar experiments. Current methods for content-based retrieval cannot address the problem of profiling...
In the Dempster-Shafer's theory of evidence, for incorporating uncertainty, the valuation assigns to the data tables the degrees of belief for these data. Firstly, we are looking for the answers to the following questions. Is there a valuation-based system in which combination and marginalization operate on valuations? Has this system prosperities analogical to the t-norm system? In the t-norm system...
Private information retrieval (PIR) protocols allow a user to retrieve a data item from a database without revealing any information about the identity of the item being retrieved. Specifically, in information-theoretic k-server PIR, the database is replicated among k non-communicating servers, and each server learns nothing about the item retrieved by the user. The cost of PIR protocols is usually...
In this paper, we describe an approach to accelerate fingerprint techniques by skipping the search for irrelevant sections of the signal and demonstrate its application to the divide and locate (DAL) audio fingerprint method. The search result for the applied method, DAL3, is the same as that of DAL mathematically. Experimental results show that DAL3 can reduce the computational cost of DAL to approximately...
Information over the web is increasingly retrieved from relational databases in which the query language is based on exact matching, data fulfil completely the query or not. The results returned to the user contain only tuples that satisfy the conditions of the query. Thereby, the user can be confronted to the problem of empty answers in the case of too selective query. To overcome this problem, several...
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,...
In this paper we present our recent work in implementing Serbian spoken dialogue system for the bus information retrieval at the main Belgrade bus station. Dialogue is organized into several levels. At each level, system has to recognize a limited number of keywords in continuous speech of Serbian. The keywords were modeled by HMMs (Hidden Markov Models) in such a way that each syllable is three-state...
Information explosion and availability of information in various forms has changed the shape of information centres and nature of information profession and professionals. Information profession and professionals have been impacted by the exponentially increasing volumes of information available — as well as with changing attitudes and behaviour of information seeker toward electronic resources. It...
Now-a-days due to increase in the availability of computing facilities, large amount of data in electronic form is been generated. The data generated is to be analyzed in order to maximize the benefit of intelligent decision making. Text categorization is an important and extensively studied problem in machine learning. The basic phases in the text categorization include preprocessing features like...
Phishing is an activity that is carried out online inorder to steal the identity of the users online such as their user IDs, passwords and credit card details. Unaware online users easily fall for these phishing web pages because of their high similarities to the real ones. Detecting & Identifying fake websites is a very cumbersome task. Several attributes are needed to be taken into consideration...
In today's world, the amount of stored information has been enormously increasing day by day which is generally in the unstructured form and cannot be used for any processing to extract useful information, so several techniques such as summarization, classification, clustering, information extraction and visualization are available for the same which comes under the category of text mining. Text Mining...
Financial fines imposed by regulatory bodies to penalize illegal activities and violations against regulations (cases of non-compliance) have recently become more common, and the sizes of fines have increased. This development coincides with the ongoing increase of complexity of regulatory rules. Huge fines have been imposed on banks for financial fraud and regulations have been made more stringent...
Nowadays, it is more demanded for techniques that are efficient in retrieval of small results from large data sets. Iceberg queries are such a kind of queries which accepts large data as input and process them for retrieve small results upon user specified threshold (T). Earlier, the iceberg queries are processed by many ways but are compromised in speed with which the data is retrieved. Thus lots...
The purpose of Text Mining is to process unstructured (textual) information, extracting meaningful numeric indices from the text, and, thus, make the information contained in the text accessible to the various data mining (statistical and machine learning) algorithms. Information can be extracted to derive summaries for the words contained in the documents or to compute summaries for the documents...
In recent years, information is increasing exponentially which makes it more and more difficult for people to find the needed information from the huge database. To fulfill this demanding, a high accurate and fast-time document retrieval algorithm is highly required for current applications. In this paper, based on the document similarity maximum criterion, we propose a new fast-time document retrieval...
Domain — specific search focuses on one area of knowledge. Applying broad based ranking algorithms to vertical search domains is not desirable. The broad based ranking model builds upon the data from multiple domains existing on the web. Vertical search engines attempt to use a focused crawler that index only relevant web pages to a predefined topic. With Ranking Adaptation Model, one can adapt an...
Recently, unstructured data like texts, documents, or SNS messages has been increasingly being used in many applications, rather than structured data consisting of simple numbers or characters. Thus it becomes more important to analysis unstructured text data to extract valuable information for usres decision making. Like OLAP (On-Line Analytical Processing) analysis over structured data, Multi-dimensional...
Private Information Retrieval (PIR) allows users to retrieve information from a database without revealing the content of these queries to anyone. The traditional information- theoretic PIR schemes utilize multiple servers to download single data block, thus incur high communication overhead and high computation burden. In this paper, we develop an Information- theoretic multi-block PIR scheme that...
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