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Fast Snippet Generation Based On CPU-GPU Hybrid System
"... Abstract—As an important part of searching result presentation, query-biased document snippet generation has become a popular method of search engines that makes the result list more informative to users. Generating a single snippet is a lightweight task. However, it will be a heavy workload to gene ..."
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Abstract—As an important part of searching result presentation, query-biased document snippet generation has become a popular method of search engines that makes the result list more informative to users. Generating a single snippet is a lightweight task. However, it will be a heavy workload
HULTECH at the NTCIR-11 Temporalia Task: Ensemble Learning for Temporal Query Intent Classification
"... This paper describes the HULTECH system of the NTCIR-11 Temporal Query Intent Classification (TQIC) subtask. Given a query string, the task is to assign one of the four temporal classes i.e. Past, Recency, Future or Atemporal. In particular, we experimented an ensemble learning paradigm, whose under ..."
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Cited by 1 (0 self)
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underlying idea is to reduce bias by combining multi-ple classifiers instead of a single one. We considered 11 types of features from three different information sources (Tem-poWordNet, Web snippets results, the query itself seen as a sentence) and used a subset of them for our submitted runs. Our system
Using Word Clouds to Summarize Multiple Search Results
"... Search engine result pages (SERPs) are known as the most expensive real estate on the planet. Most queries yield millions of organic search results, yet searchers seldom look beyond the first handful of results. To make things worse, different searchers with different query intents may issue the exa ..."
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the exact same query. An alternative to showing individual web pages summarized by snippets is to represent a whole group of results. In this paper we investigate if we can use word clouds to summarize groups of documents, e.g. to give a preview of the next result page, or of clusters of topically related
On caption bias in interleaving experiments
- In CIKM ’12. ACM
"... Information retrieval evaluation most often involves manually as-sessing the relevance of particular query-document pairs. In cases where this is difficult (such as personalized search), interleaved comparison methods are becoming increasingly common. These methods compare pairs of ranking functions ..."
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Cited by 5 (4 self)
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functions based on user clicks on search results, thus better reflecting true user preferences. How-ever, by depending on clicks, there is a potential for bias. For ex-ample, users have been previously shown to be more likely to click on results with attractive titles and snippets. An interleaving eval
Personalized click model through collaborative filtering.
- In Proceedings of WSDM.
, 2012
"... ABSTRACT Click modeling aims to interpret the users' search click data in order to predict their clicking behavior. Existing models can well characterize the position bias of documents and snippets in relation to users' mainstream click behavior. Yet, current advances depict users' s ..."
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Cited by 10 (0 self)
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ABSTRACT Click modeling aims to interpret the users' search click data in order to predict their clicking behavior. Existing models can well characterize the position bias of documents and snippets in relation to users' mainstream click behavior. Yet, current advances depict users
Word Clouds of Multiple Search Results
"... Abstract. Search engine result pages (SERPs) are known as the most expensive real estate on the planet. Most queries yield millions of organic search results, yet searchers seldom look beyond the first handful of results. To make things worse, different searchers with different query intents may iss ..."
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Cited by 1 (1 self)
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issue the exact same query. An alternative to showing individual web pages summarized by snippets is to represent whole group of results. In this paper we investigate if we can use word clouds to summarize groups of documents, e.g. to give a preview of the next SERP, or clusters of topically related
Captions and Biases in Diagnostic Search
"... People frequently turn to the Web with the goal of diagnosing medical symptoms. Studies have shown that diagnostic search can often lead to anxiety about the possibility that symptoms are explained by the presence of rare, serious medical disorders, rather than far more common benign syndromes. We s ..."
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study the influence of the appearance of potentially-alarming content, such as severe illnesses or serious treatment options associated with the queried for symptoms, in captions comprising titles, snippets, and URLs. We explore whether users are drawn to results with potentially-alarming caption
