Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval最新文献_第4页

Efficient manifold ranking for image retrieval 用于图像检索的高效流形排序

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009988

Bin Xu, Jiajun Bu, Chun Chen, Deng Cai, Xiaofei He, W. Liu, Jiebo Luo

{"title":"Efficient manifold ranking for image retrieval","authors":"Bin Xu, Jiajun Bu, Chun Chen, Deng Cai, Xiaofei He, W. Liu, Jiebo Luo","doi":"10.1145/2009916.2009988","DOIUrl":"https://doi.org/10.1145/2009916.2009988","url":null,"abstract":"Manifold Ranking (MR), a graph-based ranking algorithm, has been widely applied in information retrieval and shown to have excellent performance and feasibility on a variety of data types. Particularly, it has been successfully applied to content-based image retrieval, because of its outstanding ability to discover underlying geometrical structure of the given image database. However, manifold ranking is computationally very expensive, both in graph construction and ranking computation stages, which significantly limits its applicability to very large data sets. In this paper, we extend the original manifold ranking algorithm and propose a new framework named Efficient Manifold Ranking (EMR). We aim to address the shortcomings of MR from two perspectives: scalable graph construction and efficient computation. Specifically, we build an anchor graph on the data set instead of the traditional k-nearest neighbor graph, and design a new form of adjacency matrix utilized to speed up the ranking computation. The experimental results on a real world image database demonstrate the effectiveness and efficiency of our proposed method. With a comparable performance to the original manifold ranking, our method significantly reduces the computational time, makes it a promising method to large scale real world retrieval problems.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"22 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":"130984027","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: 139

Cognitive coordinating behaviors in multitasking web search 多任务网络搜索中的认知协调行为

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010077

J. Du

引用次数: 1

User behavior in zero-recall ecommerce queries 零召回电子商务查询中的用户行为

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009930

Gyanit Singh, Nish Parikh, Neel Sundaresan

引用次数: 13

Posting list intersection on multicore architectures 在多核架构上发布列表交集

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010045

S. Tatikonda, B. B. Cambazoglu, F. Junqueira

{"title":"Posting list intersection on multicore architectures","authors":"S. Tatikonda, B. B. Cambazoglu, F. Junqueira","doi":"10.1145/2009916.2010045","DOIUrl":"https://doi.org/10.1145/2009916.2010045","url":null,"abstract":"In current commercial Web search engines, queries are processed in the conjunctive mode, which requires the search engine to compute the intersection of a number of posting lists to determine the documents matching all query terms. In practice, the intersection operation takes a significant fraction of the query processing time, for some queries dominating the total query latency. Hence, efficient posting list intersection is critical for achieving short query latencies. In this work, we focus on improving the performance of posting list intersection by leveraging the compute capabilities of recent multicore systems. To this end, we consider various coarse-grained and fine-grained parallelization models for list intersection. Specifically, we present an algorithm that partitions the work associated with a given query into a number of small and independent tasks that are subsequently processed in parallel. Through a detailed empirical analysis of these alternative models, we demonstrate that exploiting parallelism at the finest-level of granularity is critical to achieve the best performance on multicore systems. On an eight-core system, the fine-grained parallelization method is able to achieve more than five times reduction in average query processing time while still exploiting the parallelism for high query throughput.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"259 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":"127655166","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

Temporal latent semantic analysis for collaboratively generated content: preliminary results 协作生成内容的时间潜在语义分析:初步结果

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010091

Yu Wang, Eugene Agichtein

引用次数: 7

Link formation analysis in microblogs 微博中的链接形成分析

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010136

Dawei Yin, Liangjie Hong, Xiong Xiong, Brian D. Davison

引用次数: 44

Evaluating diversified search results using per-intent graded relevance 使用每个意图分级相关性评估多样化的搜索结果

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010055

T. Sakai, Ruihua Song

{"title":"Evaluating diversified search results using per-intent graded relevance","authors":"T. Sakai, Ruihua Song","doi":"10.1145/2009916.2010055","DOIUrl":"https://doi.org/10.1145/2009916.2010055","url":null,"abstract":"Search queries are often ambiguous and/or underspecified. To accomodate different user needs, search result diversification has received attention in the past few years. Accordingly, several new metrics for evaluating diversification have been proposed, but their properties are little understood. We compare the properties of existing metrics given the premises that (1) queries may have multiple intents; (2) the likelihood of each intent given a query is available; and (3) graded relevance assessments are available for each intent. We compare a wide range of traditional and diversified IR metrics after adding graded relevance assessments to the TREC 2009 Web track diversity task test collection which originally had binary relevance assessments. Our primary criterion is discriminative power, which represents the reliability of a metric in an experiment. Our results show that diversified IR experiments with a given number of topics can be as reliable as traditional IR experiments with the same number of topics, provided that the right metrics are used. Moreover, we compare the intuitiveness of diversified IR metrics by closely examining the actual ranked lists from TREC. We show that a family of metrics called D#-measures have several advantages over other metrics such as α-nDCG and Intent-Aware metrics.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"68 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":"114359985","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: 163

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

Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization 基于非负矩阵三因子分解的双知识迁移跨语言网页分类

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2010041

Hua Wang, Heng Huang, F. Nie, C. Ding

{"title":"Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization","authors":"Hua Wang, Heng Huang, F. Nie, C. Ding","doi":"10.1145/2009916.2010041","DOIUrl":"https://doi.org/10.1145/2009916.2010041","url":null,"abstract":"The lack of sufficient labeled Web pages in many languages, especially for those uncommonly used ones, presents a great challenge to traditional supervised classification methods to achieve satisfactory Web page classification performance. To address this, we propose a novel Nonnegative Matrix Tri-factorization (NMTF) based Dual Knowledge Transfer (DKT) approach for cross-language Web page classification, which is based on the following two important observations. First, we observe that Web pages for a same topic from different languages usually share some common semantic patterns, though in different representation forms. Second, we also observe that the associations between word clusters and Web page classes are a more reliable carrier than raw words to transfer knowledge across languages. With these recognitions, we attempt to transfer knowledge from the auxiliary language, in which abundant labeled Web pages are available, to target languages, in which we want classify Web pages, through two different paths: word cluster approximations and the associations between word clusters and Web page classes. Due to the reinforcement between these two different knowledge transfer paths, our approach can achieve better classification accuracy. We evaluate the proposed approach in extensive experiments using a real world cross-language Web page data set. Promising results demonstrate the effectiveness of our approach that is consistent with our theoretical analyses.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"7 4 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":"131803834","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: 82

UPS: efficient privacy protection in personalized web search UPS:个性化网页搜索中高效的隐私保护

Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval Pub Date : 2011-07-24 DOI: 10.1145/2009916.2009999

Gang Chen, He Bai, L. Shou, Ke Chen, Yunjun Gao

引用次数: 58