Learning to Rank for Consumer Health Search: A Semantic Approach
نویسندگان
چکیده
For many internet users, searching for health advice online is the first step in seeking treatment. We present a Learning to Rank system that uses a novel set of syntactic and semantic features to improve consumer health search. Our approach was evaluated on the 2016 CLEF eHealth dataset, outperforming the best method by 26.6% in NDCG@10.
منابع مشابه
Word clustering effect on vocabulary learning of EFL learners: A case of semantic versus phonological clustering
The aim of this study is to determine the effect of word clustering method on vocabulary learning of Iranian EFL learners through a case of semantic versus phonological clustering. To this effect, 80 homogeneous students from four intermediate classes at an English institute in Torbat e Heydariyeh participated in this research. They were assigned to four groups according to semantic versus phon...
متن کاملSemi-Supervised Evaluation of Search Engines via Semantic Mapping
Content and link information is used by virtually all search engines to crawl, index, retrieve, and rank Web pages. The correlations between similarity measures based on these cues and on semantic associations between pages is crucial in determining the performance of any search tool. A great deal of research is under way to understand how to effectively extract semantic information from Web pa...
متن کاملExamining the Impact of Keyword Ambiguity on Search Advertising Performance: A Topic Model Approach
In this paper, we explore how keyword ambiguity can affect search advertising performance. Consumers arrive at search engines with diverse interests, which are often unobserved and nontrivial to predict. The search interests of different consumers may vary even when they are searching using the same keyword. In our study, we propose an automatic way of examining keyword ambiguity based on proba...
متن کاملSemantic Searching and Ranking of Documents using Hybrid Learning System and WordNet
Semantic searching seeks to improve search accuracy of the search engine by understanding searcher’s intent and the contextual meaning of the terms present in the query to retrieve more relevant results. To find out the semantic similarity between the query terms, WordNet is used as the underlying reference database. Various approaches of Learning to Rank are compared. A new hybrid learning sys...
متن کاملA Monte Carlo-Based Search Strategy for Dimensionality Reduction in Performance Tuning Parameters
Redundant and irrelevant features in high dimensional data increase the complexity in underlying mathematical models. It is necessary to conduct pre-processing steps that search for the most relevant features in order to reduce the dimensionality of the data. This study made use of a meta-heuristic search approach which uses lightweight random simulations to balance between the exploitation of ...
متن کامل