Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval最新文献_第5页

People searching for people: analysis of a people search engine log 人搜索人:分析人搜索引擎日志

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009927

W. Weerkamp, R. Berendsen, B. Kovachev, E. Meij, K. Balog, M. de Rijke

{"title":"People searching for people: analysis of a people search engine log","authors":"W. Weerkamp, R. Berendsen, B. Kovachev, E. Meij, K. Balog, M. de Rijke","doi":"10.1145/2009916.2009927","DOIUrl":"https://doi.org/10.1145/2009916.2009927","url":null,"abstract":"Recent years show an increasing interest in vertical search: searching within a particular type of information. Understanding what people search for in these \"verticals\" gives direction to research and provides pointers for the search engines themselves. In this paper we analyze the search logs of one particular vertical: people search engines. Based on an extensive analysis of the logs of a search engine geared towards finding people, we propose a classification scheme for people search at three levels: (a) queries, (b) sessions, and (c) users. For queries, we identify three types, (i) event-based high-profile queries (people that become \"popular\" because of an event happening), (ii) regular high-profile queries (celebrities), and (iii) low-profile queries (other, less-known people). We present experiments on automatic classification of queries. On the session level, we observe five types: (i) family sessions (users looking for relatives), (ii) event sessions (querying the main players of an event), (iii) spotting sessions (trying to \"spot\" different celebrities online), (iv) polymerous sessions (sessions without a clear relation between queries), and (v) repetitive sessions (query refinement and copying). Finally, for users we identify four types: (i) monitors, (ii) spotters, (iii) followers, and (iv) polymers. Our findings not only offer insight into search behavior in people search engines, but they are also useful to identify future research directions and to provide pointers for search engine improvements.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114171397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 46

The economics in interactive information retrieval 交互式信息检索中的经济学

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009923

L. Azzopardi

{"title":"The economics in interactive information retrieval","authors":"L. Azzopardi","doi":"10.1145/2009916.2009923","DOIUrl":"https://doi.org/10.1145/2009916.2009923","url":null,"abstract":"Searching is inherently an interactive process usually requiring numerous iterations of querying and assessing in order to find the desired amount of relevant information. Essentially, the search process can be viewed as a combination of inputs (queries and assessments) which are used to \"produce\" output (relevance). Under this view, it is possible to adapt microeconomic theory to analyze and understand the dynamics of Interactive Information Retrieval. In this paper, we approach the search process as an economics problem and conduct extensive simulations on TREC test collections analyzing various combinations of inputs in the \"production\" of relevance. The analysis reveals that the total Cumulative Gain (output) obtained during the course of a search session is functionally related to querying and assessing (inputs), and this can be characterized mathematically by the Cobbs-Douglas production function. Further analysis using cost models, that are grounded using cognitive load as the cost, reveals which search strategies minimize the cost of interaction for a given level of output. This paper demonstrates how economics can be applied to formally model the search process. This development establishes the theoretical foundations of Interactive Information Retrieval, providing numerous directions for empirical experimentation that are motivated directly from theory.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124676345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 111

A toolkit for knowledge base population 知识库人口的工具包

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010153

Zheng Chen, S. Tamang, Adam Lee, Heng Ji

引用次数: 3

SCENE: a scalable two-stage personalized news recommendation system SCENE:一个可扩展的两阶段个性化新闻推荐系统

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009937

Lei Li, Dingding Wang, Tao Li, Daniel Knox, B. Padmanabhan

{"title":"SCENE: a scalable two-stage personalized news recommendation system","authors":"Lei Li, Dingding Wang, Tao Li, Daniel Knox, B. Padmanabhan","doi":"10.1145/2009916.2009937","DOIUrl":"https://doi.org/10.1145/2009916.2009937","url":null,"abstract":"Recommending news articles has become a promising research direction as the Internet provides fast access to real-time information from multiple sources around the world. Traditional news recommendation systems strive to adapt their services to individual users by virtue of both user and news content information. However, the latent relationships among different news items, and the special properties of new articles, such as short shelf lives and value of immediacy, render the previous approaches inefficient. In this paper, we propose a scalable two-stage personalized news recommendation approach with a two-level representation, which considers the exclusive characteristics (e.g., news content, access patterns, named entities, popularity and recency) of news items when performing recommendation. Also, a principled framework for news selection based on the intrinsic property of user interest is presented, with a good balance between the novelty and diversity of the recommended result. Extensive empirical experiments on a collection of news articles obtained from various news websites demonstrate the efficacy and efficiency of our approach.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"88 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126309673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 233

Collective entity linking in web text: a graph-based method 网络文本中的集体实体链接:一种基于图形的方法

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010019

Xianpei Han, Le Sun, Jun Zhao

{"title":"Collective entity linking in web text: a graph-based method","authors":"Xianpei Han, Le Sun, Jun Zhao","doi":"10.1145/2009916.2010019","DOIUrl":"https://doi.org/10.1145/2009916.2010019","url":null,"abstract":"Entity Linking (EL) is the task of linking name mentions in Web text with their referent entities in a knowledge base. Traditional EL methods usually link name mentions in a document by assuming them to be independent. However, there is often additional interdependence between different EL decisions, i.e., the entities in the same document should be semantically related to each other. In these cases, Collective Entity Linking, in which the name mentions in the same document are linked jointly by exploiting the interdependence between them, can improve the entity linking accuracy. This paper proposes a graph-based collective EL method, which can model and exploit the global interdependence between different EL decisions. Specifically, we first propose a graph-based representation, called Referent Graph, which can model the global interdependence between different EL decisions. Then we propose a collective inference algorithm, which can jointly infer the referent entities of all name mentions by exploiting the interdependence captured in Referent Graph. The key benefit of our method comes from: 1) The global interdependence model of EL decisions; 2) The purely collective nature of the inference algorithm, in which evidence for related EL decisions can be reinforced into high-probability decisions. Experimental results show that our method can achieve significant performance improvement over the traditional EL methods.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125708015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 413

Learning to rank for freshness and relevance 学习根据新鲜度和相关性进行排名

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009933

Na Dai, Milad Shokouhi, Brian D. Davison

引用次数: 79

What deliberately degrading search quality tells us about discount functions 故意降低搜索质量告诉我们什么是折扣功能

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010072

Paul Thomas, Timothy Jones, D. Hawking

引用次数: 6

Persistence in the ephemeral: utilizing repeat behaviors for multi-session personalized search 短暂的持久性:利用重复行为进行多会话个性化搜索

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010175

Sarah K. Tyler

引用次数: 0

Future of the web and search 网络和搜索的未来

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009918

Qi Lu

引用次数: 0

Picasso - to sing, you must close your eyes and draw 毕加索——歌唱时，你必须闭上眼睛画画

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010012

A. Stupar, S. Michel

{"title":"Picasso - to sing, you must close your eyes and draw","authors":"A. Stupar, S. Michel","doi":"10.1145/2009916.2010012","DOIUrl":"https://doi.org/10.1145/2009916.2010012","url":null,"abstract":"We study the problem of automatically assigning appropriate music pieces to a picture or, in general, series of pictures. This task, commonly referred to as soundtrack suggestion, is non-trivial as it requires a lot of human attention and a good deal of experience, with master pieces distinguished, e.g., with the Academy Award for Best Original Score. We put forward PICASSO to solve this task in a fully automated way. PICASSO makes use of genuine samples obtained from first-class contemporary movies. Hence, the training set can be arbitrarily large and is also inexpensive to obtain but still provides an excellent source of information. At query time, PICASSO employs a three-level algorithm. First, it selects for a given query image a ranking of the most similar screenshots taken, and subsequently, selects for each screenshot the most similar songs to the music played in the movie when the screenshot was taken. Last, it issues a top-K aggregation algorithm to find the overall best suitable songs available. We have created a large training set consisting of over 40,000 image/soundtrack samples obtained from 28 movies and evaluated the suitability of PICASSO by means of a user study.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121964704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19