Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Chinese Text Summarization Using a Trainable Summarizer and Latent Semantic Analysis
ICADL '02 Proceedings of the 5th International Conference on Asian Digital Libraries: Digital Libraries: People, Knowledge, and Technology
Text summarization using a trainable summarizer and latent semantic analysis
Information Processing and Management: an International Journal - Special issue: An Asian digital libraries perspective
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
Text Classification by Combining Grouping, LSA and kNN
ICIS-COMSAR '06 Proceedings of the 5th IEEE/ACIS International Conference on Computer and Information Science and 1st IEEE/ACIS International Workshop on Component-Based Software Engineering,Software Architecture and Reuse
Information and Software Technology
The complexity of richness: Media, message, and communication outcomes
Information and Management
Perceived usefulness and performance of human-to-human communications on television
Computers in Human Behavior
Perceived effectiveness of text vs. multimedia Location-Based Advertising messaging
International Journal of Mobile Communications
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Ubiquitous Healthcare Service System with Context-awareness Capability: Design and Implementation
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
Due to the increase in advertising requirements for various multi-media services, two studies were conducted to first propose an Intelligent Embedded Marketing Service System (IEMSS) and then to use this IEMSS to implement product placement strategies for idol dramas using interactive television. In study 1, the IEMSS combines TV apps, multiple agents, and multi-document summarization technologies to retrieve and store information and comments about merchandise from search engines, blogs, and forums. The IEMSS involves a multi-document summarization technique that uses the TF-IDF (term frequency-inverse document frequency), the position and an artificial neural network (ANN) to automatically generate and transmit key positive comments to the user via TV apps. The experimental results show that the IEMSS has 100% accuracy, indicating that the IEMSS is capable of helping users understand the merchandise and improving purchase intentions. In study 2, a 2 (product description messages: shown vs. not shown)x2 (online reviews: shown vs. not shown) between-subjects design was conducted to examine the effectiveness of the IEMSS in an actual application. The results of this empirical research reveal that the display of reviews of the embedded products obtained from the Internet using the IEMSS functionality provides the viewing audience of idol dramas with the opinions of others who have used the embedded product, thereby improving attitudes toward the brand and product placement and stimulating purchase intentions. In sum, the IEMSS can be successfully applied to automatic summarization for advertising. Furthermore, this approach can be considered an extension of eWOM marketing and an application of Media Richness Theory that increases the effectiveness of product placement.