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Creating knowledge requires the existence of a person or group of people who come up with new ideas, new concepts, innovative product or process, etc.. Knowledge creation can be achieved through research, innovation projects, experiments,... more
Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore,... more
In this paper, we present a survey on Fuzzy Logic (FL) applications for Knowledge Discovery (KD), focusing on Information Retrieval (IR) and Information Extraction (IE). KD has been widely used for the search of information in vague,... more
Despite the efforts made on last decades to center the process of knowledge discovery on the user, the balance between the discovery of unknown and interesting patterns is far from being reached. The discovery of association rules is a... more
Wrapper induction techniques traditionally focus on learning wrappers based on examples from one class of Web pages, i.e. from Web pages that are all similar in structure and content. Thereby, traditional wrapper induction targets the... more
Knowledge and information spanning multiple information sources, multiple media, multiple versions and multiple communities challenge the capabilities of existing knowledge and information management infrastructures by far -primarily in... more
The University of Washington participated in English Slot Filling for TAC-KBP 2014 with a system that combines its 2013 OPENIE-KBP system with the MUL-TIR extractor , which uses distant supervision from Freebase. Since OPENIE-KBP is... more
Modern educational methods emphasize the necessity to transfer knowledge instead of data or information within the educational process. Thus it is important to the educational texts supporting the educational process contain knowledge in... more
We present results of experiments with Elman recurrent neural networks (Elman, 1990) trained on a natural language processing task. The task was to learn sequences of word categories in a text derived from a primary school reader. The... more
The combination of industrial and domestic wastewater in municipal WWTPs (waste water treatment plants) may be economically profitable, but it increases the difficulty of treatment, and also has some detrimental effects on the biomass and... more
The Possible ways of representing the knowledge while acquiring knowledge from experts are termed as Knowledge Models. The process of knowledge acquisition includes elicitation, collection, analysis, modelling and validation of knowledge.... more
Fuzzy database modelling is vital for current sectors like healthcare and finance because it optimizes the accuracy and flexibility of big data analysis for decision-making. The benefits of fuzzy database modelling, such as its capacity... more
Mining Big Data is the capability of finding new useful information in complex massive datasets, that may be continuously changing and may have varied data types. Big data is helpful only when it is transformed into knowledge or useful... more
Abstract: One of the essential elements in the translator's understanding of scientific texts is the ability to link terminological units to their corresponding conceptual categories within the specialized domain. This entails... more
In non-parametric algorithms such as k-nearest neighbour the fundamental predicaments are the larger storage and computational requirements. Moreover, the effectiveness of classification task affected significantly due to uneven... more
As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large... more
This project presents the patterns and relations between attributes of Iran Higher Education data gained from the use of data mining techniques to discover knowledge and use them in decision making system of IHE. Large dataset of IHE is... more
Huge databases are being used in organizations to store data. These databases contain hidden patterns which can be discovered and used in the organizations. In this project, we applied data mining techniques to uncover the patterns in the... more
Data Science aims to infer knowledge from facts and evidence expressed from data. This occurs through a knowledge discovery process (KDD), which requires an understanding of the application domain. However, in practice, not enough time is... more
Purpose: This study aims to develop a model for an intelligent knowledge extraction map to create value in organizations, with a focus on the service sector. Method: This is applied research. Ten influential components in knowledge... more
This paper presents a search engine system for sensor time series data and metadata in the context of building management. It takes natural language queries as input and retrieves sensor time series data, ranks them with respect to their... more
Named Entity Recognition (NER) is a challenging and widely studied task that involves detecting and typing entities in text. So far, NER still approaches entity typing as a task of classification into universal classes (e.g. date, person,... more
The role of university administrators in the use of social media within higher education institutions remains an underexplored area of academic research. While much of the existing literature has focused on students' and faculty members'... more
In an age of exponential research growth and digital dissemination, maintaining the quality and integrity of academic publishing has become increasingly challenging, particularly in the technology and information systems domains. Rising... more
The integration of artificial intelligence (AI) into religious settings is a rapidly evolving phenomenon that raises profound theological, ethical, and cultural questions. As AI-driven tools increasingly intersect with faith-based... more
Online questionnaire-based research is growing at a fast pace. Mouse-tracking methods provide a potentially important data source for this research by enabling the capture of respondents' online behaviour while answering questionnaire... more
Pointer-tracking methods can capture a real-time trace at high spatio-temporal resolution of users' pointer interactions with a graphical user interface. This trace is potentially valuable for research on human-computer interaction (HCI)... more
There is growing interest in the field of human-computer interaction in the use of mouse movement data to infer e.g. user's interests, preferences and personality. Previous work has defined various patterns of mouse movement behavior.... more
Occupational disorders considerably impact workers’ quality of life and organizational productivity, and even affect mortality worldwide. Such health issues are related to mental health and ergonomics risk factors. In particular, mental... more
Pointer-tracking methods can capture a real-time trace at high spatio-temporal resolution of users' pointer interactions with a graphical user interface. This trace is potentially valuable for research on human-computer interaction (HCI)... more
Information extraction (IE) plays very important role in natural language processing (NLP) and is fundamental to many NLP applications that used to extract structured information from unstructured text data. Heuristic-based searching and... more
It is our great pleasure to welcome you to the first edition of WWW 2018 Journal Track. The track is new track within WWW conference series and it is intended as a forum for presentations of significant Web-related research results that... more
Background In shared decision-making, a key step is quantifying the patient's preferences in relation to all the possible outcomes of the compared clinical options. According to utility theory, this can be done by eliciting utility... more
In this paper, we present a new framework to extract knowledge from today's non-semantic web. It associates semantics with the information extracted, which improves agent interoperability; it can also deal with changes to the structure of... more
Process discovery methods have obtained remarkable achievements in Process Mining, delivering comprehensible process models to enhance management capabilities. However, selecting the suitable method for a specific event log highly relies... more
In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF, OWL). With the... more
The need for learning from databases has increased along with their number and size. The new eld of Knowledge Discovery in Databases KDD develops methods that discover relevant knowledge in very large databases. Machine learning,... more
Past experiences have shown t hat there is a strong connection between Knowledge Discovery in Databases and Knowledge Visualization. This connection is twofold. On the one hand, Visualization can serve as a powerful tool for identifying... more
Actionable Knowledge Discovery approaches to extract the business and technical significant actions/patterns to support direct decision making. These actions suggest how to transform an object from an undesirable status to a desirable... more
This paper explores a hybrid approach of intrusion detection through knowledge discovery from big data using Latent Dirichlet Allocation (LDA). We identify the "hidden" patterns of operations conducted by both normal users and malicious... more
Discovering knowledge from data stored in typical alphanumeric databases, such as relational databases, has been the focal point of most of the work in database mining. However, with advances in secondary and tertiary storage capacity,... more
In this paper, we propose a framework of the whole process of churn prediction of credit card holder. In order to make the knowledge extracted from data mining more executable, we take the execution of the model into account during the... more
Mining and searching heterogeneous and large knowledge graphs is challenging under real-world resource constraints such as response time. This paper studies a framework that discover to facilitate knowledge graph search. 1) We introduce a... more
The United Nations prescribed the Sustainable Development Goals (SDGs) to various nations to provide enduring answers to widespread problems and to give long-lasting solutions to common issues being faced across the globe. SDG 5 in... more
Due to the limitation of the methodologies of traditional data mining to satisfy business expectations, the shift from mining data-centered hidden patterns to domain-driven actionable knowledge discovery has become a significant direction... more
In the UK the connection of generation to the distribution network is set to increase leading to various technical problems. This paper discusses some of the problems with existing protection schemes and describes one new approach to... more
Even though Hepatitis C Virus (HCV) cDNA was characterized about 20 years ago, there is insufficient understanding of the molecular etiology underlying HCV infections. Current global rates of infection and its increasingly chronic... more
The results of feature selection methods have a great they usually obtain better results. The hybrid model attempts to influence on the success of data mining processes, especially take advantage of the two models by exploiting their... more
We propose a robust hybrid text mining solution that combines Open Information Extraction (OIE), Knowledge Discovery from Databases (KDD) and Association Rules Mining (ARM) methods to perform domain independent text mining task. For OIE,... more