Foundations and Trends in Information Retrieval最新文献_第5页

Contextual Search: A Computational Framework 上下文搜索:一个计算框架

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2012-10-08 DOI: 10.1561/1500000023

M. Melucci

引用次数: 41

Expertise Retrieval 专业知识检索

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2012-08-12 DOI: 10.1561/1500000024

K. Balog, Yi Fang, M. de Rijke, P. Serdyukov, Luo Si

{"title":"Expertise Retrieval","authors":"K. Balog, Yi Fang, M. de Rijke, P. Serdyukov, Luo Si","doi":"10.1561/1500000024","DOIUrl":"https://doi.org/10.1561/1500000024","url":null,"abstract":"People have looked for experts since before the advent of computers. With advances in information retrieval technology and the large-scale availability of digital traces of knowledge-related activities, computer systems that can fully automate the process of locating expertise have become a reality. The past decade has witnessed tremendous interest, and a wealth of results, in expertise retrieval as an emerging subdiscipline in information retrieval. This survey highlights advances in models and algorithms relevant to this field. We draw connections among methods proposed in the literature and summarize them in five groups of basic approaches. These serve as the building blocks for more advanced models that arise when we consider a range of content-based factors that may impact the strength of association between a topic and a person. We also discuss practical aspects of building an expert search system and present applications of the technology in other domains, such as blog distillation and entity retrieval. The limitations of current approaches are also pointed out. We end our survey with a set of conjectures on what the future may hold for expertise retrieval research.","PeriodicalId":48829,"journal":{"name":"Foundations and Trends in Information Retrieval","volume":"2 1","pages":"127-256"},"PeriodicalIF":10.4,"publicationDate":"2012-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84257898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 227

Information Retrieval on the Blogosphere 博客圈的信息检索

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2012-08-01 DOI: 10.1561/1500000026

Rodrygo L. T. Santos, C. Macdonald, R. McCreadie, I. Ounis, I. Soboroff

{"title":"Information Retrieval on the Blogosphere","authors":"Rodrygo L. T. Santos, C. Macdonald, R. McCreadie, I. Ounis, I. Soboroff","doi":"10.1561/1500000026","DOIUrl":"https://doi.org/10.1561/1500000026","url":null,"abstract":"Blogs have recently emerged as a new open, rapidly evolving and reactive publishing medium on the Web. Rather than managed by a central entity, the content on the blogosphere — the collection of all blogs on the Web — is produced by millions of independent bloggers, who can write about virtually anything. This open publishing paradigm has led to a growing mass of user-generated content on the Web, which can vary tremendously both in format and quality when looked at in isolation, but which can also reveal interesting patterns when observed in aggregation. One field particularly interested in studying how information is produced, consumed, and searched in the blogosphere is information retrieval. In this survey, we review the published literature on searching the blogosphere. In particular, we describe the phenomenon of blogging and the motivations for searching for information on blogs. We cover both the search tasks underlying blog searchers' information needs and the most successful approaches to these tasks. These include blog post and full blog search tasks, as well as blog-aided search tasks, such as trend and market analysis. Finally, we also describe the publicly available resources that support research on searching the blogosphere.","PeriodicalId":48829,"journal":{"name":"Foundations and Trends in Information Retrieval","volume":"38 1","pages":"1-125"},"PeriodicalIF":10.4,"publicationDate":"2012-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76898614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Spoken Content Retrieval: A Survey of Techniques and Technologies 口语内容检索:技术与技术综述

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2012-02-23 DOI: 10.1561/1500000020

M. Larson, G. Jones

引用次数: 81

Federated Search 联邦搜索

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2011-03-05 DOI: 10.1561/1500000010

Milad Shokouhi, Luo Si

{"title":"Federated Search","authors":"Milad Shokouhi, Luo Si","doi":"10.1561/1500000010","DOIUrl":"https://doi.org/10.1561/1500000010","url":null,"abstract":"Federated search (federated information retrieval or distributed information retrieval) is a technique for searching multiple text collections simultaneously. Queries are submitted to a subset of collections that are most likely to return relevant answers. The results returned by selected collections are integrated and merged into a single list. Federated search is preferred over centralized search alternatives in many environments. For example, commercial search engines such as Google cannot easily index uncrawlable hidden web collections while federated search systems can search the contents of hidden web collections without crawling. In enterprise environments, where each organization maintains an independent search engine, federated search techniques can provide parallel search over multiple collections. \u0000 \u0000There are three major challenges in federated search. For each query, a subset of collections that are most likely to return relevant documents are selected. This creates the collection selection problem. To be able to select suitable collections, federated search systems need to acquire some knowledge about the contents of each collection, creating the collection representation problem. The results returned from the selected collections are merged before the final presentation to the user. This final step is the result merging problem. \u0000 \u0000The goal of this work, is to provide a comprehensive summary of the previous research on the federated search challenges described above.","PeriodicalId":48829,"journal":{"name":"Foundations and Trends in Information Retrieval","volume":"30 1","pages":"1-102"},"PeriodicalIF":10.4,"publicationDate":"2011-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77818433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 167

Adversarial Web Search 对抗性网络搜索

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2011-01-09 DOI: 10.1561/1500000021

C. Castillo, Brian D. Davison

{"title":"Adversarial Web Search","authors":"C. Castillo, Brian D. Davison","doi":"10.1561/1500000021","DOIUrl":"https://doi.org/10.1561/1500000021","url":null,"abstract":"Web search engines have become indispensable tools for finding content. As the popularity of the Web has increased, the efforts to exploit the Web for commercial, social, or political advantage have grown, making it harder for search engines to discriminate between truthful signals of content quality and deceptive attempts to game search engines' rankings. This problem is further complicated by the open nature of the Web, which allows anyone to write and publish anything, and by the fact that search engines must analyze ever-growing numbers of Web pages. Moreover, increasing expectations of users, who over time rely on Web search for information needs related to more aspects of their lives, further deepen the need for search engines to develop effective counter-measures against deception. \u0000 \u0000In this monograph, we consider the effects of the adversarial relationship between search systems and those who wish to manipulate them, a field known as \"Adversarial Information Retrieval\". We show that search engine spammers create false content and misleading links to lure unsuspecting visitors to pages filled with advertisements or malware. We also examine work over the past decade or so that aims to discover such spamming activities to get spam pages removed or their effect on the quality of the results reduced. \u0000 \u0000Research in Adversarial Information Retrieval has been evolving over time, and currently continues both in traditional areas (e.g., link spam) and newer areas, such as click fraud and spam in social media, demonstrating that this conflict is far from over.","PeriodicalId":48829,"journal":{"name":"Foundations and Trends in Information Retrieval","volume":"1 1","pages":"377-486"},"PeriodicalIF":10.4,"publicationDate":"2011-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80485931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 116

Automatic Summarization 自动摘要

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2011-01-01 DOI: 10.1561/1500000015

A. Nenkova, S. Maskey, Yang Liu

{"title":"Automatic Summarization","authors":"A. Nenkova, S. Maskey, Yang Liu","doi":"10.1561/1500000015","DOIUrl":"https://doi.org/10.1561/1500000015","url":null,"abstract":"It has now been 50 years since the publication of Luhn’s seminal paper on automatic summarization. During these years the practical need for automatic summarization has become increasingly urgent and numerous papers have been published on the topic. As a result, it has become harder to find a single reference that gives an overview of past efforts or a complete view of summarization tasks and necessary system components. This article attempts to fill this void by providing a comprehensive overview of research in summarization, including the more traditional efforts in sentence extraction as well as the most novel recent approaches for determining important content, for domain and genre specific summarization and for evaluation of summarization. We also discuss the challenges that remain open, in particular the need for language generation and deeper semantic understanding of language that would be necessary for future advances in the field. We would like to thank the anonymous reviewers, our students and Noemie Elhadad, Hongyan Jing, Julia Hirschberg, Annie Louis, Smaranda Muresan and Dragomir Radev for their helpful feedback. This paper was supported in part by the U.S. National Science Foundation (NSF) under IIS-05-34871 and CAREER 09-53445. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. Full text available at: http://dx.doi.org/10.1561/1500000015","PeriodicalId":48829,"journal":{"name":"Foundations and Trends in Information Retrieval","volume":"32 1","pages":"103-233"},"PeriodicalIF":10.4,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78665747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 427

Test Collection Based Evaluation of Information Retrieval Systems 基于测试集合的信息检索系统评价

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2010-06-03 DOI: 10.1561/1500000009

M. Sanderson

引用次数: 399

Web Crawling Web爬行

IF 10.4 2区计算机科学

Foundations and Trends in Information Retrieval Pub Date : 2010-03-01 DOI: 10.1561/1500000017

Christopher Olston, Marc Najork

引用次数: 2

Mining Query Logs: Turning Search Usage Data into Knowledge 挖掘查询日志:将搜索使用数据转化为知识