PAT-tree-based keyword extraction for Chinese information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Mining Text Using Keyword Distributions
Journal of Intelligent Information Systems
Information retrieval and artificial intelligence
Artificial Intelligence - Special issue on applications of artificial intelligence
Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
SearchPad: explicit capture of search context to support Web search
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Mining web logs for prediction models in WWW caching and prefetching
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Learning to find answers to questions on the Web
ACM Transactions on Internet Technology (TOIT)
Methods for comparing rankings of search engine results
Computer Networks: The International Journal of Computer and Telecommunications Networking - Web dynamics
On the peninsula phenomenon in web graph and its implications on web search
Computer Networks: The International Journal of Computer and Telecommunications Networking
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Evaluating Variable-Length Markov Chain Models for Analysis of User Web Navigation Sessions
IEEE Transactions on Knowledge and Data Engineering
Using lexical chains for keyword extraction
Information Processing and Management: an International Journal
Word AdHoc Network: Using Google Core Distance to extract the most relevant information
Knowledge-Based Systems
Using Google latent semantic distance to extract the most relevant information
Expert Systems with Applications: An International Journal
Hit count reliability: how much can we trust hit counts?
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
| Hi-index | 12.05 |
In this paper, we present a new approach to help users using search engines without entering any keywords. What we want to do is to predict what word the users may want to search before they think about it. Most of the studies done in this field focus on how to help users enter keywords or how to re-rank the search results in order to make them more precise. Both of those methods need to establish a user behavior model and a repository in which to save the logs. In our proposed method, we use the Google similarity distance to measure keywords in the Webpage to find the potential keywords for the users. Thus, we do not need any repository. All the executions are on-line and real-time. Then, we extract all the important keywords as the potential search keywords. In this way, we can use these professional keywords to achieve precise search results. We believe that this can be useful in many areas such as e-learning and can also be used in mobile devices.