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To effectively reuse existing NC machining process of similar part and feature, an effective data mining approach of existing CAM models in machining process data is proposed. First, a machining feature based multilevel structured CAM model is proposed to reveal the relations between machining features and machining operations. Then, the structured machining know-how database is automatically generated...
Learning analytics (LA) leverages learner-related data to generate reliable and factual information for the purpose of enhancing decision making in higher education, workplace and schools. Therefore, we have envisioned the need for a learning analytics system for a consortium of Nigerian universities that could serve as a tool for academic advising. The system should be able to offer advice at several...
In biology, text-mining is widely used to extract relationships between biological entities. Gene prioritization is also important to analyze diseases, because mutated or dysregulated genes play an important role in pathogenesis. Here, we propose a method to identify disease-related genes using seed genes and network analysis. We constructed an integrating gene network for lung cancer by combining...
Using formal concept analysis, we propose a method for engineering ontology from MongoDB to effectively represent unstructured data. Our method consists of three main phases: (1) generating formal context from a MongoDB, (2) applying formal concept analysis to derive a concept lattice from that formal context, and (3) converting the obtained concept lattice to the first prototype of an ontology. We...
In this paper, we propose a Markov Chain Approach to big data ranking systems. In doing so first, we create a transition matrix which will store a calculated score between every applicable pair of nodes on a large scale network. We then compute the stationary distribution of the Markov Chain with the transition matrix and rank the outcomes of this matrix to get the most influential users on the network...
The paper proposes a methodology for the development of a marketing decision support system using Big Data technology and data mining techniques. The approach was inspired by the CRISP-DM methodology, which is not oriented towards Big Data projects. Therefore, we have modified this methodology with respect to the purpose and technological requirements of the project. The proposed methodology was tested...
The aim of this paper is to show the strengths and the weakness of process mining tools in post-delivery validation. This is illustrated on two use-cases from a real-world system. We also indicate what type of research has to be done to make process mining tools more usable for validation purposes.
Correct identity recognition based on a voice sample must deal with many problems such as too big or small distance from the microphone, noise or abnormal voice. Hoarseness, coughing or even stuttering can also be encountered as disturbance of the voice. Research on new aspects of intelligent processing for voice brings possibilities to use intelligent methods to increase efficiency in processing...
The use of tattoos as a soft biometric is increasing in popularity among law enforcement communities. There is great need for large scale, publicly available tattoo datasets that can be used to standardize efforts to develop tattoo-based biometric systems. In this work, we introduce a large tattoo dataset (WVU-MediaTatt) collected from a social-media website. Additionally, we provide the source links...
Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online...
Forecasting and analyzing urban car traffic is an actual but still very complex problem. The modern car fleet handling IT systems designed for taxi and delivery service companies allows GPS coordinate data acquisition from large amount of vehicles for optimizing the ride and freight allocation. Since the database of these companies contains movement patterns belonging to multitude of vehicles, arise...
Most modern search engines feature keyword based search interfaces. These interfaces are usually found on websites belonging to enterprises or governments or sites related to news articles, blogs and social media that contain a large corpus of documents. These collections of documents are not easily indexed by web search engines, and are considered as hidden web databases. These databases provide...
Developing new ideas and algorithms or comparing new findings in the field of requirements engineering and management implies a dataset to work with. Collecting the required data is time consuming, tedious, and may involve unforeseen difficulties. The need for datasets often forces re-searchers to collect data themselves in order to evaluate their findings. However, comparing results with other publications...
Nowadays, under the circumstance of open innovation, R&D organizations of dual-coupled mode have been used in China to solve such problems existing in R&D organizations as repetition and fragmentation of institutions and research programs, low commercialization rate of scientific research results, single operating mode and the phenomenon of research lagging behind the development of industry...
In this work, we analyze the usefulness of the normalized compression distance (NCD) as a similarity measure to bird species identification through audio samples. As a first approach we review the effect of different compression methods from 7z and CompLearn Toolkit, over subsets of bird audio samples obtained from the xeno-canto database. The performance of each compression method was measured applying...
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...
Sequential pattern mining is a data mining technique that aims to extract and analyze frequent subsequences from sequences of events or items with time constraint. Sequence data mining was introduced in 1995 with the well-known Apriori algorithm. The algorithm studied the transactions through time, in order to extract frequent patterns from the sequences of products related to a customer. Later, this...
Microservices have become a popular pattern for deploying scale-out application logic and are used at companies like Netflix, IBM, and Google. An advantage of using microservices is their loose coupling, which leads to agile and rapid evolution, and continuous re-deployment. However, developers are tasked with managing this evolution and largely do so manually by continuously collecting and evaluating...
Frappé is a code comprehension tool developed by Oracle Labs that extracts the code dependencies from a codebase and stores them in a graph database enabling advanced comprehension tasks. In addition to traditional text-based queries, such context-sensitive tools allow developers to express navigational queries of the form Does function X or something it calls write to global variable Y? providing...
Nowadays, expansion of social media and internet are driving to a whole another level. Most of the users critically review anything on the internet specially foods and services in restaurants to showcase their humble opinion. These opinions are very valuable in decision making process. Analyzing and extracting the actual opinion throughout these reviews manually is practically difficult since there...
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