A Study on Support Method of Consulting Service Using Text Mining

2018 ◽  
Vol 12 (4) ◽  
pp. 482-491 ◽  
Author(s):  
Ruriko Watanabe ◽  
Nobutada Fujii ◽  
Daisuke Kokuryo ◽  
Toshiya Kaihara ◽  
Yoichi Abe ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Text Mining ◽  
Support System ◽  
Call Center ◽  
Computer Experiments ◽  
Text Data ◽  
Consulting Services ◽  
Customer Information ◽  
Wide Range ◽  
Problem Detection

This study aims to build a support method for consulting service companies allowing them to respond to client demands regardless of the expertise of the consultants. With an emphasis on the revitalization of small and medium-sized enterprises, the importance of support systems for consulting services for small and medium-sized enterprises, which support solving problems that are difficult to deal with by an enterprise, is increasing. Consulting companies can respond to a wide range of management consultations; however, because the contents of a consultation are widely and highly specialized, a service proposal and the problem detection depend on the experience and intuition of the consultant, and thus a stable service may occasionally not be provided. Therefore, a support system for providing stable services independent of the ability of consultants is desired. In this research, as the first step in constructing a support system, an analysis of customer information describing the content of a consultation with the client companies is conducted to predict the occurrence of future problems. Text data such as the consultant’s visitation history, consultation content by e-mail, and call center content are used in the analysis because the contents explain not only the current problems but also possibly contain future problems. This paper describes a method for analyzing the text data by employing text mining. In the proposed method, by combining a correspondence analysis with a DEA (Data Envelopment Analysis) discriminant analysis, words that are strongly related to problem detection are extracted from a large number of words obtained from text data, and variables of the DEA discriminant analysis are reduced and analyzed. The proposed method focuses on a cancellation of contract problems. The cancellation problem does not include uncertainty; it is clearly known whether the contract of the consulting service is being updated or cancelled. In this study, computer experiments were conducted to verify the effectiveness of the proposed method through a comparison with an existing method. The results of the verification experiment are as follows. First, there is a possibility of discovering new factors that cannot be determined from the intuition and experience of the consultant regarding the target problem. Second, through a comparison with the existing method, the effectiveness of the proposed method was confirmed.

Text Mining to Support Consulting Services for Client Company State Recognition

2020 ◽  
Vol 14 (5) ◽  
pp. 779-790
Author(s):  
Ruriko Watanabe ◽  
Nobutada Fujii ◽  
Daisuke Kokuryo ◽  
Toshiya Kaihara ◽  
Yoichi Abe ◽  
...  
Keyword(s):  
Text Mining ◽  
Support System ◽  
Computer Experiments ◽  
Text Data ◽  
Logistic Regression Models ◽  
Service Companies ◽  
Consulting Services ◽  
Customer Information ◽  
Problem Detection ◽  
Specialized Service

This study was conducted to devise a method for supporting consulting service companies in their response to client demands irrespective of the expertise of consultants. With emphasis on revitalization of small and medium-sized enterprises, the importance of support systems for consulting services to serve them is increasing. Those systems must support solutions to difficulties that must be addressed by enterprises. Consulting companies can respond to widely various management consultations. Nevertheless, because the consultation contents are highly specialized, service proposals and problem detection depend on the experience and intuition of the consultant. Often, stable service cannot be provided. A support system must provide stable services independent of the ability of consultants. In this study, analyzing customer information describing the contents of consultation with client companies is the first step in constructing a support system that can predict future problems. Text data such as a consultant’s visit history, consultation contents by e-mail, and contents of call centers are used for analyses because the contents can explain current problems. They might also indicate future problems. This report describes a method to analyze text data using text mining. The target problem is fraud, which includes uncertainty: cases in which it is not clear whether a fraud problem has occurred with the company. To address uncertainty, a method of using logistic regression models is proposed to represent inferred values as probabilities, rather than as binary discriminated data, because the possibility exists that some misidentified companies might have some difficulty. As described herein, computer experiments are conducted to verify the effectiveness of the proposed method and to compare consultants’ forecasted and achieved results. Results of a verification experiment are presented in the following. First, the proposed method is applicable to problems including uncertainties. Secondly, the possibility exists of discovering companies with a fraud problem of which they are unaware.

The Method to Analyze Freely Described Data from Questionnaires

2009 ◽  
Vol 13 (3) ◽  
pp. 268-274 ◽  
Author(s):  
Masaomi Kimura ◽  
Keyword(s):  
Text Mining ◽  
Call Center ◽  
Clustering Algorithms ◽  
Web Pages ◽  
Research Papers ◽  
Text Data ◽  
Textual Data ◽  
The Way ◽  
Newspaper Articles

Text mining has been growing; mainly due to the need to extract useful information from vast amounts of textual data. Our target here is text data, a collection of freely described data from questionnaires. Unlike research papers, newspaper articles, call-center logs and web pages, which are usually the targets of text mining analysis, the freely described data contained in the questionnaire responses have specific characteristics, including a small number of short sentences forming individual pieces of data, while the wide variety of content precludes the applications of clustering algorithms used to classify the same. In this paper, we suggest the way to extract the opinions which are delivered by multiple respondents, based on the modification relationships included in each sentence in the freely described data. Certain applications of our method are also presented after the introduction of our approach.

scholarly journals Critical Assessment of Information Extraction Systems in Biology

2003 ◽  
Vol 4 (6) ◽  
pp. 674-677 ◽  
Author(s):  
Christian Blaschke ◽  
Lynette Hirschman ◽  
Alexander Yeh ◽  
Alfonso Valencia
Keyword(s):  
Text Mining ◽  
Text Processing ◽  
Evaluation Criteria ◽  
Literature Information ◽  
Text Data ◽  
Mining Community ◽  
Wide Range ◽  
Private Datasets ◽  
Linguistic Approaches ◽  
Biological Literature

An increasing number of groups are now working in the area of text mining, focusing on a wide range of problems and applying both statistical and linguistic approaches. However, it is not possible to compare the different approaches, because there are no common standards or evaluation criteria; in addition, the various groups are addressing different problems, often using private datasets. As a result, it is impossible to determine how well the existing systems perform, and particularly what performance level can be expected in real applications. This is similar to the situation in text processing in the late 1980s, prior to the Message Understanding Conferences (MUCs). With the introduction of a common evaluation and standardized evaluation metrics as part of these conferences, it became possible to compare approaches, to identify those techniques that did or did not work and to make progress. This progress has resulted in a common pipeline of processes and a set of shared tools available to the general research community. The field of biology is ripe for a similar experiment. Inspired by this example, the BioLINK group (Biological Literature, Information and Knowledge [1]) is organizing a CASP-like evaluation for the text data-mining community applied to biology. The two main tasks specifically address two major bottlenecks for text mining in biology: (1) the correct detection of gene and protein names in text; and (2) the extraction of functional information related to proteins based on the GO classification system. For further information and participation details, see http://www.pdg.cnb.uam.es/BioLink/BioCreative.eval.html

scholarly journals Perceptions and Attitudes towards Mules in a Group of Sodiers

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1009
Author(s):  
Javiera Lagos ◽  
Manuel Rojas ◽  
Joao B. Rodrigues ◽  
Tamara Tadich
Keyword(s):  
Text Mining ◽  
Pain Perception ◽  
Health Needs ◽  
Emotional Needs ◽  
Mountainous Areas ◽  
Working Capacity ◽  
Perceptions And Attitudes ◽  
Wide Range ◽  
Positive Correlations ◽  
Word Attention

Mules are essential for pack work in mountainous areas, but there is a lack of research on this species. This study intends to assess the perceptions, attitudes, empathy and pain perception of soldiers about mules, to understand the type of human–mule relationship. For this, a survey was applied with closed-ended questions where the empathy and pain perception tools were included and later analyzed through correlations. Open-ended questions were analyzed through text mining. A total of 73 soldiers were surveyed. They had a wide range of ages and years of experience working with equids. Significant positive correlations were found between human empathy, animal empathy and pain perception. Soldiers show a preference for working with mules over donkeys and horses. Text mining analysis shows three clusters associated with the mules’ nutritional, environmental and health needs. In the same line, relevant relations were found for the word “attention” with “load”, “food”, and “harness”. When asked what mules signify for them, two clusters were found, associated with mules’ working capacity and their role in the army. Relevant relations were found between the terms “mountain”, “support”, and “logistics”, and also between “intelligent” and “noble”. To secure mules’ behavioral and emotional needs, future training strategies should include behavior and welfare concepts.

scholarly journals Estimating the number of usability problems affecting medical devices: modelling the discovery matrix

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Vincent Vandewalle ◽  
Alexandre Caron ◽  
Coralie Delettrez ◽  
Renaud Périchon ◽  
Sylvia Pelayo ◽  
...  
Keyword(s):  
Medical Devices ◽  
Market Access ◽  
Real Life ◽  
Usability Testing ◽  
Probability Of Detection ◽  
Usability Problems ◽  
Usability Problem ◽  
Wide Range ◽  
The Matrix ◽  
Problem Detection

Abstract Background Usability testing of medical devices are mandatory for market access. The testings’ goal is to identify usability problems that could cause harm to the user or limit the device’s effectiveness. In practice, human factor engineers study participants under actual conditions of use and list the problems encountered. This results in a binary discovery matrix in which each row corresponds to a participant, and each column corresponds to a usability problem. One of the main challenges in usability testing is estimating the total number of problems, in order to assess the completeness of the discovery process. Today’s margin-based methods fit the column sums to a binomial model of problem detection. However, the discovery matrix actually observed is truncated because of undiscovered problems, which corresponds to fitting the marginal sums without the zeros. Margin-based methods fail to overcome the bias related to truncation of the matrix. The objective of the present study was to develop and test a matrix-based method for estimating the total number of usability problems. Methods The matrix-based model was based on the full discovery matrix (including unobserved columns) and not solely on a summary of the data (e.g. the margins). This model also circumvents a drawback of margin-based methods by simultaneously estimating the model’s parameters and the total number of problems. Furthermore, the matrix-based method takes account of a heterogeneous probability of detection, which reflects a real-life setting. As suggested in the usability literature, we assumed that the probability of detection had a logit-normal distribution. Results We assessed the matrix-based method’s performance in a range of settings reflecting real-life usability testing and with heterogeneous probabilities of problem detection. In our simulations, the matrix-based method improved the estimation of the number of problems (in terms of bias, consistency, and coverage probability) in a wide range of settings. We also applied our method to five real datasets from usability testing. Conclusions Estimation models (and particularly matrix-based models) are of value in estimating and monitoring the detection process during usability testing. Matrix-based models have a solid mathematical grounding and, with a view to facilitating the decision-making process for both regulators and device manufacturers, should be incorporated into current standards.

scholarly journals Modern types of consulting in the management system of an educational organisation

2021 ◽  
Vol 23 (1) ◽  
pp. 73-101
Author(s):  
I. A. Korshunov ◽  
G. A. Chakhoyan ◽  
A. M. Tyunin ◽  
E. L. Lyakhovetskaya
Keyword(s):  
Open Data ◽  
Practical Significance ◽  
Educational Organizations ◽  
Text Data ◽  
Managerial Practices ◽  
Internal Resources ◽  
External Consultants ◽  
Consulting Services ◽  
Managerial Decisions ◽  
Potential Market

Introduction. In market economy, the internal and external processes of educational organisations are becoming more complex. There is a need to identify managerial practices, which can be delegated to external consultants. The process of defining such practices is not completely studied. The application of expert support from leaders and management teams is often situational.The aim of the present research is to identify the range of managerial problems of educational organisations, which cause the need to resort to external consulting support.Methodology and research methods. The application of the method of cluster analysis of text data of periodicals allowed the authors to investigate a potential market for consulting services, to identify the modern management needs of educational organizations and the experience of their solution by external organisations. The analysis of open data of consulting organisations was carried out to identify real practices.Results. The main management problems of educational organisations and the types of consulting services necessary for their solution are considered and classified. The main approaches to defining the framework of educational consulting are highlighted. The authors have developed the method for monitoring the prospective market for consulting services. It was determined that the growing demand for consulting services and the expansion of the range of these services are associated with the formation of a market environment in the education system and the desire of management of educational organisations to provide a competitive advantage. The cases of Russian and foreign consulting organisations were analysed and grouped in accordance with the proposed typology.Scientific novelty. In academic literature, the study of this issue is mainly limited to defining the boundaries of educational consulting. The authors have made an attempt to identify typical situations, in which managers of educational organisations need to request the services of external experts.Practical significance. The results of the current research can serve as a guideline for the management of educational organisations, when making managerial decisions. It will allow the managers to determine the cases, in which it is possible to turn to external consultants according to the supply conditions on the market, and to identify the issues, regarding which it is desirable to rely solely on internal resources.

scholarly journals RK Algorithm: Stochastic Parallel Methodology for Symmetric Key Cryptography

2017 ◽  
Vol 2 (3) ◽  
pp. 137-144
Author(s):  
Yegireddi Ramesh ◽  
Kiran Kumar Reddi
Keyword(s):  
Information Age ◽  
Block Size ◽  
Large Data ◽  
Digital Information ◽  
Text Data ◽  
Plain Text ◽  
Cipher Text ◽  
Wide Range ◽  
Symmetric Key ◽  
Symmetric Key Cryptography

With the enormous growth in the Internet and network, data security has become an inevitable concern for any organization. From antecedent security has attracted considerable attention from network researchers. In this perspective many possible fields of endeavour come to mind with many cryptographic algorithms in a broader way, each is highly worthy and lengthy. As society is moving towards digital information age we necessitate highly standard algorithms which compute faster when data size is of wide range or scope. On survey, numerous sequential approaches carried out by symmetric key algorithms on 128 bits as block size are ascertained to be highly in securable and resulting at a low speed. As in the course the commodities are immensely parallelized on multi core processors to solve computational problems, in accordance with, propound parallel symmetric key based algorithms to encrypt/decrypt large data for secure conveyance. The algorithm is aimed to prevail by considering 64 character (512 bits) plain text data, processed 16 characters separately by applying parallelism and finally combine each 16 character cipher data to form 64 character cipher text. The round function employed in the algorithm is very complex, on which improves efficacy.

scholarly journals Stress and Sexual Dysfunction among Call Center Employees

2014 ◽  
Vol 1 (3) ◽  
Author(s):  
Dr. V.D. Kasture
Keyword(s):  
Sexual Dysfunction ◽  
Call Center ◽  
Call Centers ◽  
High Stress ◽  
Work Load ◽  
International Studies ◽  
Positive Thinking ◽  
Wide Range ◽  
Female Employees ◽  
Call Center Employees

The call center community often defines itself as an industry, with numerous national and international call centers. But there has some dispute among researchers as to whether it is appropriate to refer such thing as the ‘call center industry’. Bain and Taylor (1999) argue that it is more appropriate to use the term ‘sector’ as call centers are found across a wide range of industries and may be similar primarily in terms of their core technologies. Belt, Richardson and Websler (2000) agreed that call centers are not an ‘industry’ as the term generally defined, but rather represent certain ways of delivering various services using the telephone and computer technologies across traditional industry boundaries. This research results revealed that female employees from international call centers show high stress score and high sexual dysfunction than domestic call center employees, which means the female employees from international call center differed significantly (t=5.26, p=<0.01) than domestic call center female employees. Results obtained from t test showed that female employees from domestic and international call center differed significantly with one another on stress scores and sexual dysfunction. The reason is that international call center employees have more work stress as compare to that with domestic one. This due to heavy work load, not enough time for social interaction and completion of work within a given period of time. The work culture is more strict and systematic as compared to domestic one. International studies in the past have linked stress t sexual dysfunction and infertility among women. The overall results of the present study suggest the need for stress management programs for reducing the stress and developing positive thinking among young female employees working in call centers.

Incorporating Text OLAP in Business Intelligence

2011 ◽  
pp. 77-101 ◽  
Author(s):  
Byung-Kwon Park ◽  
Il-Yeol Song
Keyword(s):  
Information Retrieval ◽  
Text Mining ◽  
Business Intelligence ◽  
Multidimensional Analysis ◽  
Web Pages ◽  
Data Types ◽  
Text Documents ◽  
Text Data ◽  
Platform Architecture ◽  
Unstructured Text

As the amount of data grows very fast inside and outside of an enterprise, it is getting important to seamlessly analyze both data types for total business intelligence. The data can be classified into two categories: structured and unstructured. For getting total business intelligence, it is important to seamlessly analyze both of them. Especially, as most of business data are unstructured text documents, including the Web pages in Internet, we need a Text OLAP solution to perform multidimensional analysis of text documents in the same way as structured relational data. We first survey the representative works selected for demonstrating how the technologies of text mining and information retrieval can be applied for multidimensional analysis of text documents, because they are major technologies handling text data. And then, we survey the representative works selected for demonstrating how we can associate and consolidate both unstructured text documents and structured relation data for obtaining total business intelligence. Finally, we present a future business intelligence platform architecture as well as related research topics. We expect the proposed total heterogeneous business intelligence architecture, which integrates information retrieval, text mining, and information extraction technologies all together, including relational OLAP technologies, would make a better platform toward total business intelligence.

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