Search results for "Mining"
showing 10 items of 1730 documents
Does relevance matter to data mining research?
2008
Data mining (DM) and knowledge discovery are intelligent tools that help to accumulate and process data and make use of it. We review several existing frameworks for DM research that originate from different paradigms. These DM frameworks mainly address various DM algorithms for the different steps of the DM process. Recent research has shown that many real-world problems require integration of several DM algorithms from different paradigms in order to produce a better solution elevating the importance of practice-oriented aspects also in DM research. In this chapter we strongly emphasize that DM research should also take into account the relevance of research, not only the rigor of it. Und…
On the use of information systems research methods in data mining
2006
Information systems are powerful instruments for organizational problem solving through formal information processing (Lyytinen, 1987). Data mining (DM) and knowledge discovery are intelligent tools that help to accumulate and process data and make use of it (Fayyad, 1996). Data mining bridges many technical areas, including databases, statistics, machine learning, and human-computer interaction. The set of data mining processes used to extract and verify patterns in data is the core of the knowledge discovery process. Numerous data mining techniques have recently been developed to extract knowledge from large databases. The area of data mining is historically more related to AI (Artificial…
Knowledge management challenges in knowledge discovery systems
2006
Current knowledge discovery systems are armed with many data mining techniques that can be potentially applied to a new problem. However, a system faces a challenge of selecting the most appropriate technique(s) for a problem at hand, since in the real domain area it is infeasible to perform a comparison of all applicable techniques. The main goal of this paper is to consider the limitations of data-driven approaches and propose a knowledge-driven approach to enhance the use of multiple data-mining strategies in a knowledge discovery system. We introduce the concept of (meta-) knowledge management, which is aimed to organize a systematic process of (meta-) knowledge capture and refinement o…
Critical thinking and continuous improvement: a scientific text mining approach
2020
This work aims to propose and argue a new antecedent (critical thinking: CT) of the hard and soft dimensions of continuous improvement (CI) using a text mining perspective. The study employs a prop...
FCA-based knowledge representation and local generalized linear models to address relevance and diversity in diverse social images
2019
Abstract In social image retrieval, the main goal is to offer a relevant but also diverse result set of images to the user. To address relevance and diversity at the same time, we propose a multi-modal procedure. This approach deals with the diversification problem using a two-step procedure based on the application of Formal Concept Analysis (FCA) to organize the text content of the images, followed by a Hierarchical Agglomerative Clustering (HAC) step to find the topics addressed by the images. FCA detects the latent concepts covered by the images in the result set, organizing them according to these concepts. In the second step, clustering is carried out to group together the ones with a…
Handling Context-Sensitive Temporal Knowledge from Multiple Differently Ranked Sources
1999
In this paper we develop one way to represent and reason with temporal relations in the context of multiple experts. Every relation between temporal intervals consists of four endpoints’ relations. It is supposed that the context we know is the value of every expert competence concerning every endpoint relation. Thus the context for an interval temporal relation is one kind of compound expert’s rank, which has four components appropriate to every interval endpoints’ relation. Context is being updated after every new opinion is being added to the previous opinions about certain temporal relation. The context of a temporal relation collects all support given by different experts to all compon…
Feature Ranking of Large, Robust, and Weighted Clustering Result
2017
A clustering result needs to be interpreted and evaluated for knowledge discovery. When clustered data represents a sample from a population with known sample-to-population alignment weights, both the clustering and the evaluation techniques need to take this into account. The purpose of this article is to advance the automatic knowledge discovery from a robust clustering result on the population level. For this purpose, we derive a novel ranking method by generalizing the computation of the Kruskal-Wallis H test statistic from sample to population level with two different approaches. Application of these enlargements to both the input variables used in clustering and to metadata provides a…
Supervised vs Unsupervised Latent DirichletAllocation: topic detection in lyrics.
2020
Topic modeling is a type of statistical modeling for discovering the abstract ``topics'' that occur in a collection of documents. Latent Dirichlet Allocation (LDA) is an example of topic model and is used to classify text in a document to a particular topic. It builds a fixed number of topics starting from words in each document modeled according to a Dirichlet distribution. In this work we are going to apply LDA to a set of songs from four famous Italian songwriters and split them into topics. This work studies the use of themes in lyrics using statistical analysis to detect topics. Aim of the work is to underline the main limits of the standard unsupervised LDA and to propose a supervised…
The removal of sulphate from mine water by precipitation as ettringite and the utilisation of the precipitate as a sorbent for arsenate removal.
2016
Abstract The aim of this research was to investigate sulphate removal from mine water by precipitation as ettringite (Ca6Al2(SO4)3(OH)12·26H2O) and the utilisation of the precipitate as a sorbent for arsenate removal. The mine water sulphate concentration was reduced by 85–90% from the initial 1400 mg/L during ettringite precipitation depending on the treatment method. The precipitation conditions were also simulated with MINEQL + software, and the computational results were compared with the experimental results. The precipitated solids were characterised with X-ray diffraction and a scanning electron microscope. The precipitated solids were tested as sorbents for arsenate removal from the…
Rock decay phenomena and collapse processes in the “Latomiae del Paradiso” in Syracuse (Sicily)
2014
The Latomiae (origin: Greek latomia, from laas, las stone plus –tomia tomy ) del Paradiso in Syracuse are Magna Graecia rock quarries, located in the coastal areas of Southern Italy and internationally renowned for their impressive environment. The few historical technical records do not help clarify the events that led to their current configuration since a series of instability phenomena occurred due to decay processes over time. Through a geotechnical back-analysis, this work highlights the failure phenomena, which may have led to the current configuration of the easterly side of the Latomiae del Paradiso. The back-analysis process was carried out by means of numerical modelling, support…