Boilerplate detection using shallow text features
Proceedings of the third ACM international conference on Web search and data mining
Exploiting query reformulations for web search result diversification
Proceedings of the 19th international conference on World wide web
ACM SIGIR Forum
Proceedings of the 3rd International Semantic Search Workshop
Diversifying search results of controversial queries
Proceedings of the 20th ACM international conference on Information and knowledge management
Information Retrieval on the Blogosphere
Foundations and Trends in Information Retrieval
MOUNA: mining opinions to unveil neglected arguments
Proceedings of the 21st ACM international conference on Information and knowledge management
Sentiment diversification with different biases
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
| Hi-index | 0.00 |
This paper introduces a system enriching the standard web search engine interface with sentiment information. Additionally, it exploits such annotations to diversify the result list based on the different sentiments expressed by retrieved web pages. Thanks to the annotations, the end user is aware of which opinions the search engine is showing her and, thanks to the diversification, she can see an overview of the different opinions expressed about the requested topic. We describe the methods used for computing sentiment scores of web search results and for re-ranking them in order to cover different sentiment classes. The proposed system, built on top of commercial search engine APIs, is available on-line.