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The primary purpose of an information retrieval (IR) system is to retrieve all the relevant documents, which are relevant to the user query. Latent Semantic Indexing/Analysis (LSI/LSA) based ad hoc document retrieval task investigates the performance of retrieval systems that search a static set of documents using new questions. Performance of LSI has been tested by others for several smaller datasets...
We present a risk management framework which allows to reason about and manage risk for role based access control systems. The framework expresses essential characteristics of risk management in dynamic environments, and can be used for assessing risk and decision making; it is flexible, and able to handle different access control requirements. This framework provides a basis for designing and implementation...
In this paper, we attempt to get better insight on how Internet usage behaviors of female students in university can affect on their different academic activities also compare usage patterns of different departments' students with their teachers' patterns. In addition, we attempt to find similarities and dissimilarities of usage patterns of students on various branches and finding relationships between...
Increasingly, resources are “born digital” and their associated formats are short-lived. Subsequently, the development of environments to preserve such digital content over the very long-term (50 years or more) has become a critical issue. To date, however, the preservation of data as contained in object-relational databases has been widely overlooked. Here, the task is inherently complicated by the...
Traditional clustering methods were developed to analyse complete data sets. Faults during the data collection, data transfer or data cleaning often lead to missing values in data so that common clustering methods can not be used for the data analysis. Therefore, in these cases clustering methods which can handle missing values in data are of great use. In this paper we discuss different approaches...
Business Intelligence (BI) capitalized on data-mining and analytics techniques for discovering trends and reacting to events with quick decisions. We argued that a new breed of data-mining, namely stream-mining where continuous data streams arrive into the system and get mined very quickly, stimulates the design of a new real-time BI architecture. In the past, stream-mining (especially in algorithmic...
Data mining aims at extraction of previously unidentified information from large databases. It can be viewed as an automated application of algorithms to discover hidden patterns and to extract knowledge from data. Online Analytical Processing (OLAP) systems, on the other hand, allow exploring and querying huge datasets in interactive way. These OLAP systems are the predominant front-end tools used...
Several studies show that background knowledge of a domain can improve the results of clustering algorithms. In this paper, we illustrate how to use the background knowledge of medical domain in clustering process to predict the likelihood of diseases. To find the likelihood of diseases, clustering has to be done based on anticipated likelihood attributes with core attributes of disease in data point...
Automatic topic detection becomes more important due to the increase of information electronically available and the necessity to process and filter it. In particular, when language is noisy like in weblog postings, it is challenging to determine topics correctly. Nevertheless, it is still unclear, to what extent existing topic detection algorithms are able to deal with this noisy material. In this...
The concern about understanding the effects of climate change on the environment, such as the decline of pollinators found in nature, the need to support researchers to run experiments efficiently and to share those results, makes it necessary to study and develop virtual laboratories through the web, in order to gain greater insight on the behavior of bees, which is the main pollinator of plants...
Conventional positive association rules are the patterns that occur frequently together. These patterns represent what decisions are routinely made based on a set of facts. Irregular association rules are the patterns that represent what decisions are rarely made based on the same set of facts. Many domains like Healthcare, Banking etc need the irregular rule to improve their system. In this paper,...
Most companies have their data stored electronically. The appropriate processing of this data can quickly identify issues leading to process improvement and cost reduction. However, the manipulation of the data stored in the companies' repositories is not trivial for decision support. In this paper we propose the use of Excel spreadsheets for the detection of parameters that may cause the plastic...
High-order functions are the sole elements in a class of recursive functions. The functions are related to each other through application, i.e., applying a function to an argument yields a value where the argument and the value are also functions. Through Froglingo, a language that exactly takes advantage of high-order functions and their properties, we introduce the method of representing business...
In medical qualitative research, medical researchers analyze historical patient data to verify known relationships and to discover unknown relationships among medical attributes. All the existing algorithms to solve this problem use measures which are asymmetric measure, so only one direction of the rule (P -> Q or Q->P) is taken into account. However, medical researchers are interested to find...
The wood production is an activity of fundamental importance for Brazilian economy. Studies show that the illegality in wood production is around 80% of the total production. This illegal wood becomes legalized in its supply chain due to the failures in controlling and monitoring systems. This paper analyzes some computational problems existing in managing and monitoring the production process in...
Non-text user generated content (UGC), such as videos and images, is usually searched by metadata. Metadata, such as title, tags, and description, is created by users whenever content is uploaded. However, in many cases metadata can have multiple meanings. This requires users to spend time sifting through a long list of search results until they can find all the content for which they were actually...
Improving the relevancy of Web search results has been of increasing interest in recent years. The nature of the Web implies heterogeneity, large volumes, and varied structures. Hence, finding results that best suit the needs of every individual is a very challenging problem. Accordingly, interactive graphical and visualization techniques are suggested to increase the ability of the display to handle...
This paper addresses the Information Retrieval issues by today's hierarchical systems such as file systems. They usually contain substantial amount of redundant items. Maintaining the structure becomes difficult when large amount of items exist and ambiguity occurs in the structure. In this study, a conceptual method is presented that replaces the “containment” principle involved in current systems...
In this paper, a similarity evaluating model based on rough formal concept analysis and information content similarity is proposed which evaluates the similarity degree between the concepts. We use the information content approach to automatically obtain part of similarity scores of two concepts which makes up the normal featural and structural evaluating models. Then through our model, the similarity...
Accelerated growth of the Internet has enabled users worldwide to share their feelings and experiences. User-generated content (UGC) websites are the most abundant sources of user reviews. Accurately identifying sentiment phrases is essential to understand the expressed opinions in user reviews. To achieve this, part-of-speech (POS) patterns of phrases are useful. However, previous studies for Chinese...
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