Learning for search result diversification
Nettetmance over the state-of-the-art results. Introduction To cope with ambiguous and/or underspecified queries, search result diversification (SRD) has been regarded as the key solution and has shown significantly increasing values in a wide range of domains, such as web search (Ma, Lyu, and King 2010; Liu et al. 2014; Liang 2024) and recom- Nettet8. apr. 2024 · 6 Conclusion. In this paper, we proposed a novel graph-based implicit method for the search result diversification task. Our model first constructs a document interaction graph for each query, then models the interaction between each document and its neighbors by adopting the graph attention network.
Learning for search result diversification
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Nettet1. apr. 2024 · In this paper, we address search result diversification as a learning problem, and introduce a novel relational learning-to-rank approach to formulate the task. However, ... Nettet15. okt. 2016 · Search diversification plays an important role in modern search engine, especially when user-issued queries are ambiguous and the top ranked results are redundant. Some diversity search approaches have been proposed (e.g., Maximal Marginal Relevance (MMR) [ 1 ] and its numerous variants [ 5 , 7 , 9 ]) for reducing the …
Nettet1. jul. 2024 · Search result diversification has gained attention as a way to tackle the ambiguous or multi-faceted information needs of users. Most existing methods on this problem utilize a heuristic ... Nettet12. sep. 2024 · Abstract. Making use of search systems to foster learning is an emerging research trend known as search as learning. Earlier works identified result …
Nettet24. aug. 2014 · Personalized search result diversification via structured learning. Pages 751–760. Previous Chapter Next Chapter. ... We also define two constraints in our … Nettet22. okt. 2024 · From my perspective, diversification most likely occurs when Google spits out thematically unified search results because it’s not able to respond perfectly to a …
Nettet3. jul. 2014 · DOI: 10.1145/2600428.2609634 Corpus ID: 16248630; Learning for search result diversification @article{Zhu2014LearningFS, title={Learning for search result …
Nettet27. sep. 2010 · Result diversification has recently attracted much attention as a means of increasing user satisfaction in recommender systems and web search. Many different … ipad thinkerNettet13. apr. 2024 · Your product portfolio is not only a reflection of your brand strategy, but also a driver of it. Therefore, you should ensure that your products are aligned with your brand vision, mission, values ... ipad things 3Nettet14. apr. 2024 · Learn more about how we select deals. > Life > Education > Online Learning TL;DR: You can find a wide range of online courses (Opens in a new tab) from Harvard University for free on edX. open run/debug tool window when startedNettet14. sep. 2008 · Renjith is a FinTech industry-mature subject-matter expert, who has for many years guided both business and technical teams toward results-guaranteed performance and delivery of projects. His hands-on experience was accumulated over a 15+ year period in these industries; serving in various roles in technology companies … openrun by shokz apphttp://yadongzhu.com/papers/Learning%20for%20Search%20Result%20Diversification.pdf open run by shokz pairingNettet5. okt. 2024 · Intuitively, the relationship among the context-response sentences is similar to the that among selected-candidate documents in implicit search result diversification tasks. Inspired by previous work in multi-turn response selection, we propose an interaction-based methods for search result diversification. Fig. 1. The structure of … open run command windowNettetEvaluating Diversified Search Results Using Per-intent Graded Relevance SIGIR. Google Scholar; Rodrygo L. T. Santos, Craig Macdonald, and Iadh Ounis. 2010. … open run by shokz