Deep multimodal distance metric learning using click constraints for image ranking
How do we retrieve images accurately? Also, how do we rank a group of images precisely
and efficiently for specific queries? These problems are critical for researchers and …
and efficiently for specific queries? These problems are critical for researchers and …
Click prediction for web image reranking using multimodal sparse coding
Image reranking is effective for improving the performance of a text-based image search.
However, existing reranking algorithms are limited for two main reasons: 1) the textual meta …
However, existing reranking algorithms are limited for two main reasons: 1) the textual meta …
Learning to rank using user clicks and visual features for image retrieval
The inconsistency between textual features and visual contents can cause poor image
search results. To solve this problem, click features, which are more reliable than textual …
search results. To solve this problem, click features, which are more reliable than textual …
Learning to rank with selection bias in personal search
Click-through data has proven to be a critical resource for improving search ranking quality.
Though a large amount of click data can be easily collected by search engines, various …
Though a large amount of click data can be easily collected by search engines, various …
Best match: new relevance search for PubMed
N Fiorini, K Canese, G Starchenko, E Kireev, W Kim… - PLoS …, 2018 - journals.plos.org
PubMed is a free search engine for biomedical literature accessed by millions of users from
around the world each day. With the rapid growth of biomedical literature—about two articles …
around the world each day. With the rapid growth of biomedical literature—about two articles …
A neural click model for web search
Understanding user browsing behavior in web search is key to improving web search
effectiveness. Many click models have been proposed to explain or predict user clicks on …
effectiveness. Many click models have been proposed to explain or predict user clicks on …
When search engine services meet large language models: visions and challenges
Combining Large Language Models (LLMs) with search engine services marks a significant
shift in the field of services computing, opening up new possibilities to enhance how we …
shift in the field of services computing, opening up new possibilities to enhance how we …
Exploiting click constraints and multi-view features for image re-ranking
Image re-ranking is effective in improving performance of text-based image searches.
However, improvements from existing re-ranking algorithms are limited by two factors: one is …
However, improvements from existing re-ranking algorithms are limited by two factors: one is …
Beyond dwell time: estimating document relevance from cursor movements and other post-click searcher behavior
Q Guo, E Agichtein - Proceedings of the 21st international conference on …, 2012 - dl.acm.org
Result clickthrough statistics and dwell time on clicked results have been shown valuable for
inferring search result relevance, but the interpretation of these signals can vary …
inferring search result relevance, but the interpretation of these signals can vary …
Online evaluation for information retrieval
Online evaluation is one of the most common approaches to measure the effectiveness of an
information retrieval system. It involves fielding the information retrieval system to real users …
information retrieval system. It involves fielding the information retrieval system to real users …