Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Automatic structuring and retrieval of large text files
Communications of the ACM
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Assessing the impact of using the Internet for competitive intelligence
Information and Management
The Journal of Machine Learning Research
Text classification from unlabeled documents with bootstrapping and feature projection techniques
Information Processing and Management: an International Journal
Developing a semantic-enable information retrieval mechanism
Expert Systems with Applications: An International Journal
Direct and indirect effects of retail promotions on sales and profits in the do-it-yourself market
Expert Systems with Applications: An International Journal
Mining changes in customer behavior in retail marketing
Expert Systems with Applications: An International Journal
Customer-adapted coupon targeting using feature selection
Expert Systems with Applications: An International Journal
Extracting Consumers Needs for New Products - A Web Mining Approach
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Unified collaborative filtering model based on combination of latent features
Expert Systems with Applications: An International Journal
Mining ideas from textual information
Expert Systems with Applications: An International Journal
A semantic term weighting scheme for text categorization
Expert Systems with Applications: An International Journal
Neurocomputing
Expert Systems with Applications: An International Journal
Topics modeling based on selective Zipf distribution
Expert Systems with Applications: An International Journal
Global data mining: An empirical study of current trends, future forecasts and technology diffusions
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
User-oriented ontology-based clustering of stored memories
Expert Systems with Applications: An International Journal
Using latent topics to enhance search and recommendation in Enterprise Social Software
Expert Systems with Applications: An International Journal
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
Modeling partial customer churn: On the value of first product-category purchase sequences
Expert Systems with Applications: An International Journal
Detecting weak signals for long-term business opportunities using text mining of Web news
Expert Systems with Applications: An International Journal
Predicting e-commerce company success by mining the text of its publicly-accessible website
Expert Systems with Applications: An International Journal
Improved multilevel security with latent semantic indexing
Expert Systems with Applications: An International Journal
Using Webcrawling of Publicly Available Websites to Assess E-commerce Relationships
SRII '12 Proceedings of the 2012 Annual SRII Global Conference
Technology classification with latent semantic indexing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Protecting research and technology from espionage
Expert Systems with Applications: An International Journal
Web mining based extraction of problem solution ideas
Expert Systems with Applications: An International Journal
Quantitative cross impact analysis with latent semantic indexing
Expert Systems with Applications: An International Journal
Semantic compared cross impact analysis
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
We investigate an automated identification of weak signals according to Ansoff to improve strategic planning and technological forecasting. Literature shows that weak signals can be found in the organization's environment and that they appear in different contexts. We use internet information to represent organization's environment and we select these websites that are related to a given hypothesis. In contrast to related research, a methodology is provided that uses latent semantic indexing (LSI) for the identification of weak signals. This improves existing knowledge based approaches because LSI considers the aspects of meaning and thus, it is able to identify similar textual patterns in different contexts. A new weak signal maximization approach is introduced that replaces the commonly used prediction modeling approach in LSI. It enables to calculate the largest number of relevant weak signals represented by singular value decomposition (SVD) dimensions. A case study identifies and analyses weak signals to predict trends in the field of on-site medical oxygen production. This supports the planning of research and development (R&D) for a medical oxygen supplier. As a result, it is shown that the proposed methodology enables organizations to identify weak signals from the internet for a given hypothesis. This helps strategic planners to react ahead of time.