Detecting weak signals for long-term business opportunities using text mining of Web news

2012 ◽  
Vol 39 (16) ◽  
pp. 12543-12550 ◽  
Author(s):  
Janghyeok Yoon
Keyword(s):  
Text Mining ◽  
Weak Signals ◽  
Business Opportunities ◽  
Web News

Enhancing the Preparedness of SMEs for E-Business Opportunities by Collaborative Networks

2011 ◽  
pp. 254-270
Author(s):  
Heiko Duin ◽  
Klaus-Dieter Thoben
Keyword(s):  
Strategic Planning ◽  
Automotive Industry ◽  
Impact Analysis ◽  
Virtual Organisations ◽  
Collaborative Networks ◽  
Business Opportunity ◽  
Organisational Form ◽  
Business Opportunities ◽  
The Right

This chapter introduces virtual Organisations (VOs) as a special organisational form of collaborative networks of SMEs to conduct E-Business projects. VOs are normally not created from scratch, but instantiated from a strategic network or pool of enterprises. This enhances the preparedness of participating members when an E-Business opportunity occurs. The underlying strategic network acts as a breeding environment for the VOs. Therefore, it is called a VO Breeding Environment (VBE). Examples from the automotive industry are illustrating the development and needs of this concept. Strategic planning is important for such a network in order to increase chances of occurring business opportunities. The remainder of this chapter shows how scenario-oriented methods such as cross-impact analysis can be used to support a collaborative strategic planning in such networked organisations. The application of such methods allows long-term foresight and the anticipation of the right technological, financial and business oriented decisions.

An Application of Text Mining to Capture and Analyze eWOM

2016 ◽  
pp. 168-186 ◽  
Author(s):  
Taşkın Dirsehan
Keyword(s):  
Data Mining ◽  
Text Mining ◽  
Customer Relationship ◽  
Competitive Advantages ◽  
Strategic Decisions ◽  
Data Mining Tool ◽  
Mining Tool ◽  
The Moment ◽  
Mining Tools

Marketing concept has progressed through different phases of evolution in the past. At the moment, customer relationship management is considered as the last era of marketing development. The main purpose of this approach is to build long-term oriented profitable relationships with customers. So, companies should know better their customers. This knowledge can be created through a deeper analysis of companies' data with data mining tools. Companies which are able to use data mining tools will gain strong competitive advantages for their strategic decisions. Hotel industry is selected in this study, since it provides a warehouse of customer comments from which precious knowledge can be obtained if text mining as a data mining tool is used appropriately. Thus, this study attempts to explain the stages of text mining with the use of Rapidminer. As a result, different approaches according to the customer satisfaction/dissatisfaction are discussed to build competitive advantages.

Enhancing the Preparedness of SMEs for E-Business Opportunities by Collaborative Networks

2010 ◽  
pp. 30-45
Author(s):  
Heiko Duin ◽  
Klaus-Dieter Thoben
Keyword(s):  
Strategic Planning ◽  
Automotive Industry ◽  
Impact Analysis ◽  
Virtual Organisations ◽  
Collaborative Networks ◽  
Business Opportunity ◽  
Organisational Form ◽  
Business Opportunities ◽  
The Right

This chapter introduces virtual Organisations (VOs) as a special organisational form of collaborative networks of SMEs to conduct E-Business projects. VOs are normally not created from scratch, but instantiated from a strategic network or pool of enterprises. This enhances the preparedness of participating members when an E-Business opportunity occurs. The underlying strategic network acts as a breeding environment for the VOs. Therefore, it is called a VO Breeding Environment (VBE). Examples from the automotive industry are illustrating the development and needs of this concept. Strategic planning is important for such a network in order to increase chances of occurring business opportunities. The remainder of this chapter shows how scenario-oriented methods such as cross-impact analysis can be used to support a collaborative strategic planning in such networked organisations. The application of such methods allows long-term foresight and the anticipation of the right technological, financial and business oriented decisions.

scholarly journals Analysis of Long-term Market Trend by Text-Mining of News Articles

2013 ◽  
Vol 28 (3) ◽  
pp. 291-296 ◽  
Author(s):  
Takahisa Kuramoto ◽  
Kiyoshi Izumi ◽  
Yoshimura Shinobu ◽  
Tomonari Ishida ◽  
Akihiro Nakashima ◽  
...  
Keyword(s):  
Text Mining

A Simple Model of Long-Term Spike Train Regularization

2002 ◽  
Vol 14 (7) ◽  
pp. 1575-1597 ◽  
Author(s):  
Relly Brandman ◽  
Mark E. Nelson
Keyword(s):  
Spike Train ◽  
Threshold Model ◽  
Spike Trains ◽  
Adaptive Threshold ◽  
Nerve Fibers ◽  
Weak Signals ◽  
Spike Threshold ◽  
Afferent Nerve Fibers ◽  
Regularizing Effects

A simple model of spike generation is described that gives rise to negative correlations in the interspike interval (ISI) sequence and leads to long-term spike train regularization. This regularization can be seen by examining the variance of thekth-order interval distribution for large k (the times between spike i and spike i Ck). The variance is much smaller than would be expected if successive ISIs were uncorrelated. Such regularizing effects have been observed in the spike trains of electrosensory afferent nerve fibers and can lead to dramatic improvement in the detectability of weak signals encoded in the spike train data (Ratnam & Nelson, 2000). Here, we present a simple neural model in which negative ISI correlations and long-term spike train regularization arise from refractory effects associated with a dynamic spike threshold. Our model is derived from a more detailed model of electrosensory afferent dynamics developed recently by other investigators (Chacron, Longtin, St.-Hilaire, & Maler, 2000; Chacron, Longtin, & Maler, 2001). The core of this model is a dynamic spike threshold that is transiently elevated following a spike and subsequently decays until the next spike is generated. Here, we present a simplified version—the linear adaptive threshold model—that contains a single state variable and three free parameters that control the mean and coefficient of variation of the spontaneous ISI distribution and the frequency characteristics of the driven response. We show that refractory effects associated with the dynamic threshold lead to regularization of the spike train on long timescales. Furthermore, we show that this regularization enhances the detectability of weak signals encoded by the linear adaptive threshold model. Although inspired by properties of electrosensory afferent nerve fibers, such regularizing effects may play an important role in other neural systems where weak signals must be reliably detected in noisy spike trains. When modeling a neuronal system that exhibits this type of ISI correlation structure, the linear adaptive threshold model may

scholarly journals Keyword Network Analysis on Long Term Care Insurance Using Text Mining

2021 ◽  
Vol 46 (3) ◽  
pp. 257-266
Author(s):  
Jonggeun Seo ◽  
Chung Mo Nam ◽  
Tae Hyun Kim ◽  
So-Hee Park
Keyword(s):  
Big Data ◽  
Text Mining ◽  
Long Term Care ◽  
The Elderly ◽  
Care Providers ◽  
Data Types ◽  
Term Care ◽  
Service Institution ◽  
Long Term Care Insurance

Objectives: This study conducted research using big data in order to overcome the limitations of existing qualitative research or analysis research. By analyzing keywords, the flow and role of long-term care insurance in society were analyzed.Methods: Issues were searched through text mining, one of the big data techniques, and the flow of agendas by period was examined by 3 time points (institutional settlement period, 1st basic plan, 2nd basic plan). Using R and NetMiner, Daum News (news.daum.net) and Naver News (news.naver.com) were web-scraped to collect 20,965 news articles, 4,994 articles were filtered for keyword extraction and analysis. Result: Looking at the characteristics of each data type, in all data types, long-term care institutions (including nursing homes) and care providers appear as the top keywords, and the keyword subgroup characteristics are ① grade/service, ② institution management, and ③ the employee group includes the keyword subgroup.Conclusions: This study is based on the subject of long-term care insurance for the elderly and applies big data analysis techniques, and can be used as a decision-making tool in establishing policies and systems.

scholarly journals Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing

2020 ◽  
Vol 12 (19) ◽  
pp. 7848 ◽  
Author(s):  
Israel Griol-Barres ◽  
Sergio Milla ◽  
Antonio Cebrián ◽  
Huaan Fan ◽  
Jose Millet
Keyword(s):  
Natural Language Processing ◽  
Text Mining ◽  
Natural Language ◽  
Language Processing ◽  
Weak Signals ◽  
Remote Sensors ◽  
The Future ◽  
Increasing Demand ◽  
New Applications ◽  
Start Ups

Organizations, companies and start-ups need to cope with constant changes on the market which are difficult to predict. Therefore, the development of new systems to detect significant future changes is vital to make correct decisions in an organization and to discover new opportunities. A system based on business intelligence techniques is proposed to detect weak signals, that are related to future transcendental changes. While most known solutions are based on the use of structured data, the proposed system quantitatively detects these signals using heterogeneous and unstructured information from scientific, journalistic and social sources, applying text mining to analyze the documents and natural language processing to extract accurate results. The main contributions are that the system has been designed for any field, using different input datasets of documents, and with an automatic classification of categories for the detected keywords. In this research paper, results from the future of remote sensors are presented. Remote sensing services are providing new applications in observation and analysis of information remotely. This market is projected to witness a significant growth due to the increasing demand for services in commercial and defense industries. The system has obtained promising results, evaluated with two different methodologies, to help experts in the decision-making process and to discover new trends and opportunities.

Transformation of E-Fulfilment Industry Capabilities

2011 ◽  
pp. 1082-1088
Author(s):  
Paul Alexander ◽  
Janice M. Burn
Keyword(s):  
United States ◽  
The United States ◽  
Transformation Model ◽  
Support Tool ◽  
Business Change ◽  
Business Opportunities ◽  
New Business

Over the last decade, organisations have been forced to re-examine the role of ICT as a support tool and accept that it has become a major driver for business change (Ash & Burn, 2003, pp. 297-308.). Indeed, new business opportunities have arisen solely based on e-business: e-fulfilment is one such example (Alexander & Burn, 2004, p.1). These services were estimated to be worth US$1,006 Trillion in the United States alone, or 10.1% of their GDP in 2000 (Rogers, 2002). Furthermore, 21% of all logistics transactions are expected to be online by 2005, with the long-term possibility that traditional freight companies will ultimately cease to exist (Homs, Meringer, & Rehkopf, 2001). This article explores the concepts which are encompassed in the term e-fulfilment, and presents a model of e-fulfilment activities. This model is then validated through the analysis of e-fulfilment capabilities of 48 UK based e-fulfilment companies. The findings from this analysis lead to an extension of the model and suggest a long term transformation model for the industry as a whole.

Turkey's Economic Sustainability in Global Hypercompetition

2016 ◽  
pp. 173-184
Author(s):  
Bryan Christansen ◽  
Tuğba Dirikan ◽  
Caner Dirikan ◽  
Fatmanur Kasarcı
Keyword(s):  
Sustainable Development ◽  
Informal Economy ◽  
Direct Investment ◽  
Global Environment ◽  
Economic Sustainability ◽  
Key Factors ◽  
Business Opportunities ◽  
The Republic ◽  
Republic Of Turkey

The Republic of Turkey represents solid business opportunities for both Foreign Direct Investment (FDI) and domestic enterprises. However, the economic sustainability of these opportunities lies in several key factors such as global hypercompetition, business creativity, the informal economy, and international brand equity. While abundant talent exists in multiple industries in Turkey, a major challenge is to encourage businesspersons and government elite to harness this talent better and make it more efficient. This chapter shall explore these and other factors like human resource management and English as a Foreign Language (EFL) training to examine how the nation's long-term economic prosperity can be maintained in a global environment which demands sustainable development.

Sign in / Sign up

Export Citation Format

Share Document