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Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval最新文献

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Hashtag retrieval in a microblogging environment 微博环境中的标签检索
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835616
Miles Efron
{"title":"Hashtag retrieval in a microblogging environment","authors":"Miles Efron","doi":"10.1145/1835449.1835616","DOIUrl":"https://doi.org/10.1145/1835449.1835616","url":null,"abstract":"Microblog services let users broadcast brief textual messages to people who \"follow\" their activity. Often these posts contain terms called hashtags, markers of a post's meaning, audience, etc. This poster treats the following problem: given a user's stated topical interest, retrieve useful hashtags from microblog posts. Our premise is that a user interested in topic x might like to find hashtags that are often applied to posts about x. This poster proposes a language modeling approach to hashtag retrieval. The main contribution is a novel method of relevance feedback based on hashtags. The approach is tested on a corpus of data harvested from twitter.com.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"128 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120908366","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: 182
HCC: a hierarchical co-clustering algorithm HCC:一种分层共聚类算法
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835653
Jingxuan Li, Tao Li
{"title":"HCC: a hierarchical co-clustering algorithm","authors":"Jingxuan Li, Tao Li","doi":"10.1145/1835449.1835653","DOIUrl":"https://doi.org/10.1145/1835449.1835653","url":null,"abstract":"In this poster, we develop a novel method, called HCC, for hierarchical co-clustering. HCC brings together two interrelated but distinct themes from clustering: hierarchical clustering and co-clustering. The goal of the former theme is to organize clusters into a hierarchy that facilitates browsing and navigation, while the goal of the latter theme is to cluster different types of data simultaneously by making use of the relationship information. Our initial empirical results are promising and they demonstrate that simultaneously attempting both these goals in a single model leads to improvements over models that focus on a single goal.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121237511","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: 17
Serendipitous recommendations via innovators 来自创新者的偶然推荐
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835487
N. Kawamae
{"title":"Serendipitous recommendations via innovators","authors":"N. Kawamae","doi":"10.1145/1835449.1835487","DOIUrl":"https://doi.org/10.1145/1835449.1835487","url":null,"abstract":"To realize services that provide serendipity, this paper assesses the surprise of each user when presented recommendations. We propose a recommendation algorithm that focuses on the search time that, in the absence of any recommendation, each user would need to find a desirable and novel item by himself. Following the hypothesis that the degree of user's surprise is proportional to the estimated search time, we consider both innovators' preferences and trends for identifying items with long estimated search times. To predict which items the target user is likely to purchase in the near future, the candidate items, this algorithm weights each item that innovators have purchased and that reflect one or more current trends; it then lists them in order of decreasing weight. Experiments demonstrate that this algorithm outputs recommendations that offer high user/item coverage, a low Gini coefficient, and long estimated search times, and so offers a high degree of recommendation serendipitousness.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124769849","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: 61
Comparing click-through data to purchase decisions for retrieval evaluation 比较点击数据和购买决策，以进行检索评估
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835603
Katja Hofmann, B. Huurnink, M. Bron, M. de Rijke
{"title":"Comparing click-through data to purchase decisions for retrieval evaluation","authors":"Katja Hofmann, B. Huurnink, M. Bron, M. de Rijke","doi":"10.1145/1835449.1835603","DOIUrl":"https://doi.org/10.1145/1835449.1835603","url":null,"abstract":"Traditional retrieval evaluation uses explicit relevance judgments which are expensive to collect. Relevance assessments inferred from implicit feedback such as click-through data can be collected inexpensively, but may be less reliable. We compare assessments derived from click-through data to another source of implicit feedback that we assume to be highly indicative of relevance: purchase decisions. Evaluating retrieval runs based on a log of an audio-visual archive, we find agreement between system rankings and purchase decisions to be surprisingly high.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124907345","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: 16
Linking wikipedia to the web 将维基百科链接到网络
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835642
R. Kaptein, P. Serdyukov, J. Kamps
{"title":"Linking wikipedia to the web","authors":"R. Kaptein, P. Serdyukov, J. Kamps","doi":"10.1145/1835449.1835642","DOIUrl":"https://doi.org/10.1145/1835449.1835642","url":null,"abstract":"We investigate the task of finding links from Wikipedia pages to external web pages. Such external links significantly extend the information in Wikipedia with information from the Web at large, while retaining the encyclopedic organization of Wikipedia. We use a language modeling approach to create a full-text and anchor text runs, and experiment with different document priors. In addition we explore whether social bookmarking site Delicious can be exploited to further improve our performance. We have constructed a test collection of 53 topics, which are Wikipedia pages on different entities. Our findings are that the anchor text index is a very effective method to retrieve home pages. Url class and anchor text length priors and their combination leads to the best results. Using Delicious on its own does not lead to very good results, but it does contain valuable information. Combining the best anchor text run and the Delicious run leads to further improvements.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125384131","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: 8
Efficient partial-duplicate detection based on sequence matching 基于序列匹配的部分重复检测方法
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835562
Qi Zhang, Yue Zhang, Haomin Yu, Xuanjing Huang
{"title":"Efficient partial-duplicate detection based on sequence matching","authors":"Qi Zhang, Yue Zhang, Haomin Yu, Xuanjing Huang","doi":"10.1145/1835449.1835562","DOIUrl":"https://doi.org/10.1145/1835449.1835562","url":null,"abstract":"With the ever-increasing growth of the Internet, numerous copies of documents become serious problem for search engine, opinion mining and many other web applications. Since partial-duplicates only contain a small piece of text taken from other sources and most existing near-duplicate detection approaches focus on document level, partial duplicates can not be dealt with well. In this paper, we propose a novel algorithm to realize the partial-duplicate detection task. Besides the similarities between documents, our proposed algorithm can simultaneously locate the duplicated parts. The main idea is to divide the partial-duplicate detection task into two subtasks: sentence level near-duplicate detection and sequence matching. For evaluation, we compare the proposed method with other approaches on both English and Chinese web collections. Experimental results appear to support that our proposed method is effectively and efficiently to detect both partial-duplicates on large web collections.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"70 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125485594","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: 55
Flickr group recommendation based on tensor decomposition 基于张量分解的Flickr群组推荐
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835591
Nan Zheng, Qiudan Li, Shengcai Liao, Leiming Zhang
{"title":"Flickr group recommendation based on tensor decomposition","authors":"Nan Zheng, Qiudan Li, Shengcai Liao, Leiming Zhang","doi":"10.1145/1835449.1835591","DOIUrl":"https://doi.org/10.1145/1835449.1835591","url":null,"abstract":"Over the last few years, Flickr has gained massive popularity and groups in Flickr are one of the main ways for photo diffusion. However, the huge volume of groups brings troubles for users to decide which group to choose. In this paper, we propose a tensor decomposition-based group recommendation model to suggest groups to users which can help tackle this problem. The proposed model measures the latent associations between users and groups by considering both semantic tags and social relations. Experimental results show the usefulness of the proposed model.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114938782","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: 45
Freshness matters: in flowers, food, and web authority 新鲜度很重要:鲜花、食物和网络权威
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835471
Na Dai, Brian D. Davison
{"title":"Freshness matters: in flowers, food, and web authority","authors":"Na Dai, Brian D. Davison","doi":"10.1145/1835449.1835471","DOIUrl":"https://doi.org/10.1145/1835449.1835471","url":null,"abstract":"The collective contributions of billions of users across the globe each day result in an ever-changing web. In verticals like news and real-time search, recency is an obvious significant factor for ranking. However, traditional link-based web ranking algorithms typically run on a single web snapshot without concern for user activities associated with the dynamics of web pages and links. Therefore, a stale page popular many years ago may still achieve a high authority score due to its accumulated in-links. To remedy this situation, we propose a temporal web link-based ranking scheme, which incorporates features from historical author activities. We quantify web page freshness over time from page and in-link activity, and design a web surfer model that incorporates web freshness, based on a temporal web graph composed of multiple web snapshots at different time points. It includes authority propagation among snapshots, enabling link structures at distinct time points to influence each other when estimating web page authority. Experiments on a real-world archival web corpus show our approach improves upon PageRank in both relevance and freshness of the search results.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116035970","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: 65
A ranking approach to target detection for automatic link generation 一种自动链路生成目标检测的排序方法
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835638
Jiyin He, M. de Rijke
{"title":"A ranking approach to target detection for automatic link generation","authors":"Jiyin He, M. de Rijke","doi":"10.1145/1835449.1835638","DOIUrl":"https://doi.org/10.1145/1835449.1835638","url":null,"abstract":"We focus on the task of target detection in automatic link generation with Wikipedia, i.e., given an N-gram in a snippet of text, find the relevant Wikipedia concepts that explain or provide background knowledge for it. We formulate the task as a ranking problem and investigate the effectiveness of learning to rank approaches and of the features that we use to rank the target concepts for a given N-gram. Our experiments show that learning to rank approaches outperform traditional binary classification approaches. Also, our proposed features are effective both in binary classification and learning to rank settings.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116559000","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: 9
Hierarchical pitman-yor language model for information retrieval 信息检索的分层pitman-yor语言模型
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2010-07-19 DOI: 10.1145/1835449.1835619
S. Momtazi, D. Klakow
{"title":"Hierarchical pitman-yor language model for information retrieval","authors":"S. Momtazi, D. Klakow","doi":"10.1145/1835449.1835619","DOIUrl":"https://doi.org/10.1145/1835449.1835619","url":null,"abstract":"In this paper, we propose a new application of Bayesian language model based on Pitman-Yor process for information retrieval. This model is a generalization of the Dirichlet distribution. The Pitman-Yor process creates a power-law distribution which is one of the statistical properties of word frequency in natural language. Our experiments on Robust04 indicate that this model improves the document retrieval performance compared to the commonly used Dirichlet prior and absolute discounting smoothing techniques.","PeriodicalId":378368,"journal":{"name":"Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130568774","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: 12
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