Motivation: Recognizing words that are key to a document is important for ranking relevant scientific documents. Traditionally, important words in a document are either nominated subjectively by authors and indexers or selected objectively by some statistical measures. As an alternative, we propose to use documents ’ words popularity in user queries to identify click-words, a set of prominent words from the users ’ perspective. Although they often overlap, click-words differ significantly from other document keywords. Results: We developed a machine learning approach to learn the unique characteristics of click-words. Each word was represented by a set of features that included different types of information, such as semantic type, part of ...
Objective: In 2016, the International Agency for Research on Cancer, part of the World Health Organi...
Understanding users ’ search intents is critical component of modern search engines. A key limitatio...
The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/a1...
Abstract: The PubMed search engine displays query results in reverse chronological order, which is a...
MOTIVATION: It would be useful to be able to retrieve a ranked publication list relevant to topics o...
The semantic gap between low-level visual features and high-level semantics has been investigated fo...
The semantic gap between low-level visual features and high-level semantics has been investigated fo...
Author-supplied citations are a fraction of the related literature for a paper. The ‘‘related citati...
There are several problems regarding information retrieval on biomedical in-formation. The common me...
Motivation: The recent explosion of interest in mining the biomedical literature for associations be...
There are several problems regarding information retrieval on biomedical information. The common met...
The keyphrase extraction task is a fundamental and challenging task designed to automatically extrac...
AbstractSearch engines typically estimate relevance using features of the documents. We believe that...
The keyphrase extraction task is a fundamental and challenging task designed to automatically extrac...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
Objective: In 2016, the International Agency for Research on Cancer, part of the World Health Organi...
Understanding users ’ search intents is critical component of modern search engines. A key limitatio...
The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/a1...
Abstract: The PubMed search engine displays query results in reverse chronological order, which is a...
MOTIVATION: It would be useful to be able to retrieve a ranked publication list relevant to topics o...
The semantic gap between low-level visual features and high-level semantics has been investigated fo...
The semantic gap between low-level visual features and high-level semantics has been investigated fo...
Author-supplied citations are a fraction of the related literature for a paper. The ‘‘related citati...
There are several problems regarding information retrieval on biomedical in-formation. The common me...
Motivation: The recent explosion of interest in mining the biomedical literature for associations be...
There are several problems regarding information retrieval on biomedical information. The common met...
The keyphrase extraction task is a fundamental and challenging task designed to automatically extrac...
AbstractSearch engines typically estimate relevance using features of the documents. We believe that...
The keyphrase extraction task is a fundamental and challenging task designed to automatically extrac...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
Objective: In 2016, the International Agency for Research on Cancer, part of the World Health Organi...
Understanding users ’ search intents is critical component of modern search engines. A key limitatio...
The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/a1...