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Traditional machine-learned ranking systems for web search are often trained to capture stationary relevance of documents to queries, which has limited ability to track non-stationary user intention in a timely manner. In recency search,…

Information Retrieval · Computer Science 2011-03-22 Taesup Moon , Wei Chu , Lihong Li , Zhaohui Zheng , Yi Chang

This paper concerns corpus poisoning attacks in dense information retrieval, where an adversary attempts to compromise the ranking performance of a search algorithm by injecting a small number of maliciously generated documents into the…

Information Retrieval · Computer Science 2026-03-17 Yongkang Li , Panagiotis Eustratiadis , Simon Lupart , Evangelos Kanoulas

Search engines play an essential role in our daily lives. Nonetheless, they are also very crucial in enterprise domain to access documents from various information sources. Since traditional search systems index the documents mainly by…

Information Retrieval · Computer Science 2021-12-30 Gizem Gezici

Search engines perform the task of retrieving information related to the user-supplied query words. This task has two parts; one is finding "featured words" which describe an article best and the other is finding a match among these words…

Neural and Evolutionary Computing · Computer Science 2007-05-23 A. Das , M. Marko , A. Probst , M. A. Porter , C. Gershenson

Retrieving keywords (bidwords) with the same intent as query, referred to as close variant keywords, is of prime importance for effective targeted search advertising. For head and torso search queries, sponsored search engines use a huge…

Computation and Language · Computer Science 2021-06-08 Akash Kumar Mohankumar , Nikit Begwani , Amit Singh

Context information in search sessions has proven to be useful for capturing user search intent. Existing studies explored user behavior sequences in sessions in different ways to enhance query suggestion or document ranking. However, a…

Information Retrieval · Computer Science 2021-08-25 Yutao Zhu , Jian-Yun Nie , Zhicheng Dou , Zhengyi Ma , Xinyu Zhang , Pan Du , Xiaochen Zuo , Hao Jiang

Google's PageRank has created a new synergy to information retrieval for a better ranking of Web pages. It ranks documents depending on the topology of the graphs and the weights of the nodes. PageRank has significantly advanced the field…

Digital Libraries · Computer Science 2010-12-23 Ying Ding , Erjia Yan , Arthur Frazho , James Caverlee

The task of creating indicative summaries that help a searcher decide whether to read a particular document is a difficult task. This paper examines the indicative summarization task from a generation perspective, by first analyzing its…

Computation and Language · Computer Science 2007-05-23 Min-Yen Kan , Kathleen R. McKeown , Judith L. Klavans

In web search, typically a candidate generation step selects a small set of documents---from collections containing as many as billions of web pages---that are subsequently ranked and pruned before being presented to the user. In Bing, the…

Information Retrieval · Computer Science 2018-08-21 Corby Rosset , Damien Jose , Gargi Ghosh , Bhaskar Mitra , Saurabh Tiwary

Domain expertise is regarded as one of the key factors impacting search success: experts are known to write more effective queries, to select the right results on the result page, and to find answers satisfying their information needs.…

Information Retrieval · Computer Science 2015-12-23 Julia Kiseleva , Alejandro Montes García , Jaap Kamps , Nikita Spirin

Search engines could consistently favor certain values over the others, which is considered as biased due to the built-in infrastructures. Many studies have been dedicated to detect, control, and mitigate the impacts of the biases from the…

Information Retrieval · Computer Science 2021-05-10 Bin Han , Chirag Shah , Daniel Saelid

We present GenEx, a generative model to explain search results to users beyond just showing matches between query and document words. Adding GenEx explanations to search results greatly impacts user satisfaction and search performance.…

Information Retrieval · Computer Science 2021-11-03 Razieh Rahimi , Youngwoo Kim , Hamed Zamani , James Allan

Search engine results often misalign with users' goals due to opaque algorithms, leading to unhelpful or detrimental information consumption. To address this, we developed a Google Chrome plugin that provides "content labels" for webpages…

Human-Computer Interaction · Computer Science 2024-10-08 Christopher Kelly , Jonatan Fontanez , Tali Sharot

Many online platforms predominantly rank items by predicted user engagement. We believe that there is much unrealized potential in including non-engagement signals, which can improve outcomes both for platforms and for society as a whole.…

Social and Information Networks · Computer Science 2024-02-13 Tom Cunningham , Sana Pandey , Leif Sigerson , Jonathan Stray , Jeff Allen , Bonnie Barrilleaux , Ravi Iyer , Smitha Milli , Mohit Kothari , Behnam Rezaei

In this paper we discuss several issues related to automated text classification of web sites. We analyze the nature of web content and metadata in relation to requirements for text features. We find that HTML metatags are a good source of…

Information Retrieval · Computer Science 2007-05-23 John M. Pierre

While a plethora of hypertext links exist on the Web, only a small amount of them are regularly clicked. Starting from this observation, we set out to study large-scale click data from Wikipedia in order to understand what makes a link…

Social and Information Networks · Computer Science 2017-02-21 Dimitar Dimitrov , Philipp Singer , Florian Lemmerich , Markus Strohmaier

In classical causal inference, inferring cause-effect relations from data relies on the assumption that units are independent and identically distributed. This assumption is violated in settings where units are related through a network of…

Artificial Intelligence · Computer Science 2022-07-05 Razieh Nabi , Joel Pfeiffer , Murat Ali Bayir , Denis Charles , Emre Kıcıman

As the use of web is increasing more day by day, the web users get easily lost in the web's rich hyper structure. The main aim of the owner of the website is to give the relevant information according their needs to the users. We explained…

Information Retrieval · Computer Science 2012-08-10 Laxmi Choudhary , Bhawani Shankar Burdak

For many queries in the Web retrieval setting there is an on-going ranking competition: authors manipulate their documents so as to promote them in rankings. Such competitions can have unwarranted effects not only in terms of retrieval…

Information Retrieval · Computer Science 2018-06-14 Gregory Goren , Oren Kurland , Moshe Tennenholtz , Fiana Raiber

Social media is increasingly being used as a news-platform. To reach their intended audience, newspapers need for their articles to be well ranked by Facebook's news-feed algorithm. The number of likes, shares and other reactions determine…

Computers and Society · Computer Science 2019-11-01 Marc Faddoul
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