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Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval最新文献

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Document retrieval from user-selected web sites 从用户选择的网站检索文档
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860558
U. Bohnacker, Ingrid Renz
{"title":"Document retrieval from user-selected web sites","authors":"U. Bohnacker, Ingrid Renz","doi":"10.1145/860435.860558","DOIUrl":"https://doi.org/10.1145/860435.860558","url":null,"abstract":"We present a new tool for gathering textual information according to a query (texts) on arbitrary web sites specified by an information-seeking user. This tool is helpful in any knowledge-intensive area. Its technology is based on the vector space model with optimized feature definition. .","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117220792","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: 1
Probabilistic structured query methods 概率结构化查询方法
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860497
Kareem Darwish, Douglas W. Oard
{"title":"Probabilistic structured query methods","authors":"Kareem Darwish, Douglas W. Oard","doi":"10.1145/860435.860497","DOIUrl":"https://doi.org/10.1145/860435.860497","url":null,"abstract":"Structured methods for query term replacement rely on separate estimates of term tes of replacement probabilities. Statistically significantfrequency and document frequency to compute a weight for each query term. This paper reviews prior work on structured query techniques and introduces three new variants that leverage estima improvements in retrieval effectiveness are demonstrated for cross-language retrieval and for retrieval based on optical character recognition when replacement probabilities are used to estimate both term frequency and document frequency.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"382 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116522404","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: 128
On an equivalence between PLSI and LDA PLSI与LDA的等价性
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860537
M. Girolami, A. Kabán
{"title":"On an equivalence between PLSI and LDA","authors":"M. Girolami, A. Kabán","doi":"10.1145/860435.860537","DOIUrl":"https://doi.org/10.1145/860435.860537","url":null,"abstract":"Latent Dirichlet Allocation (LDA) is a fully generative approach to language modelling which overcomes the inconsistent generative semantics of Probabilistic Latent Semantic Indexing (PLSI). This paper shows that PLSI is a maximum a posteriori estimated LDA model under a uniform Dirichlet prior, therefore the perceived shortcomings of PLSI can be resolved and elucidated within the LDA framework.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124196463","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: 232
Stuff I've seen: a system for personal information retrieval and re-use 我见过的东西:个人信息检索和再利用系统
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860451
S. Dumais, Edward Cutrell, Jonathan J. Cadiz, Gavin Jancke, Raman Sarin, Daniel C. Robbins
{"title":"Stuff I've seen: a system for personal information retrieval and re-use","authors":"S. Dumais, Edward Cutrell, Jonathan J. Cadiz, Gavin Jancke, Raman Sarin, Daniel C. Robbins","doi":"10.1145/860435.860451","DOIUrl":"https://doi.org/10.1145/860435.860451","url":null,"abstract":"Most information retrieval technologies are designed to facilitate information discovery. However, much knowledge work involves finding and re-using previously seen information. We describe the design and evaluation of a system, called Stuff I've Seen (SIS), that facilitates information re-use. This is accomplished in two ways. First, the system provides a unified index of information that a person has seen, whether it was seen as email, web page, document, appointment, etc. Second, because the information has been seen before, rich contextual cues can be used in the search interface. The system has been used internally by more than 230 employees. We report on both qualitative and quantitative aspects of system use. Initial findings show that time and people are important retrieval cues. Users find information more easily using SIS, and use other search tools less frequently after installation.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122748617","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: 76
When query expansion fails 当查询扩展失败时
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860514
B. Billerbeck, J. Zobel
{"title":"When query expansion fails","authors":"B. Billerbeck, J. Zobel","doi":"10.1145/860435.860514","DOIUrl":"https://doi.org/10.1145/860435.860514","url":null,"abstract":"The effectiveness of queries in information retrieval can be improved through query expansion. This technique automatically introduces additional query terms that are statistically likely to match documents on the intended topic. However, query expansion techniques rely on fixed parameters. Our investigation of the effect of varying these parameters shows that the strategy of using fixed values is questionable.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124805497","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: 24
Empirical development of an exponential probabilistic model for text retrieval: using textual analysis to build a better model 文本检索的指数概率模型的实证发展:利用文本分析建立一个更好的模型
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860441
J. Teevan, David R Karger
{"title":"Empirical development of an exponential probabilistic model for text retrieval: using textual analysis to build a better model","authors":"J. Teevan, David R Karger","doi":"10.1145/860435.860441","DOIUrl":"https://doi.org/10.1145/860435.860441","url":null,"abstract":"Much work in information retrieval focuses on using a model of documents and queries to derive retrieval algorithms. Model based development is a useful alternative to heuristic development because in a model the assumptions are explicit and can be examined and refined independent of the particular retrieval algorithm. We explore the explicit assumptions underlying the naïve framework by performing computational analysis of actual corpora and queries to devise a generative document model that closely matches text. Our thesis is that a model so developed will be more accurate than existing models, and thus more useful in retrieval, as well as other applications. We test this by learning from a corpus the best document model. We find the learned model better predicts the existence of text data and has improved performance on certain IR tasks.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122151345","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: 27
A personalised information retrieval tool 一个个性化的信息检索工具
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860532
I. Martin, J. Jose
{"title":"A personalised information retrieval tool","authors":"I. Martin, J. Jose","doi":"10.1145/860435.860532","DOIUrl":"https://doi.org/10.1145/860435.860532","url":null,"abstract":"Industry professionals and everyday users of the Internet have long accepted that due to both the size and growth of this ubiquitous repository, new tools are needed to assist with the finding and extraction of very specific resources relevant to a user's task. Previously, this definition of relevance has been based on the extremely generic matching between resources and query terms, but recently the emphasis is shifting towards a more personalised model based on the relevance of a particular resource for one specific user. We introduce a prototype, tt Fetch, which adopts this concept within an information-seeking environment specifically designed to provide users with the means to better describe a problem (s)he doesn't understand.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127811287","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
User-trainable video annotation using multimodal cues 用户可训练的视频注释使用多模态线索
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860522
Ching-Yung Lin, M. Naphade, A. Natsev, C. Neti, John R. Smith, Belle L. Tseng, H. Nock, W. H. Adams
{"title":"User-trainable video annotation using multimodal cues","authors":"Ching-Yung Lin, M. Naphade, A. Natsev, C. Neti, John R. Smith, Belle L. Tseng, H. Nock, W. H. Adams","doi":"10.1145/860435.860522","DOIUrl":"https://doi.org/10.1145/860435.860522","url":null,"abstract":"This paper describes progress towards a general framework for incorporating multimodal cues into a trainable system for automatically annotating user-defined semantic concepts in broadcast video. Models of arbitrary concepts are constructed by building classifiers in a score space defined by a pre-deployed set of multimodal models. Results show annotation for user-defined concepts both in and outside the pre-deployed set is competitive with our best video-only models on the TREC Video 2002 corpus. An interesting side result shows speech-only models give performance comparable to our best video-only models for detecting visual concepts such as \"outdoors\", \"face\" and \"cityscape\".","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127994856","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: 10
Domain-independent text segmentation using anisotropic diffusion and dynamic programming 基于各向异性扩散和动态规划的领域无关文本分割
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860494
Xiang-Hua Ji, H. Zha
{"title":"Domain-independent text segmentation using anisotropic diffusion and dynamic programming","authors":"Xiang-Hua Ji, H. Zha","doi":"10.1145/860435.860494","DOIUrl":"https://doi.org/10.1145/860435.860494","url":null,"abstract":"This paper presents a novel domain-independent text segmentation method, which identifies the boundaries of topic changes in long text documents and/or text streams. The method consists of three components: As a preprocessing step, we eliminate the document-dependent stop words as well as the generic stop words before the sentence similarity is computed. This step assists in the discrimination of the sentence semantic information. Then the cohesion information of sentences in a document or a text stream is captured with a sentence-distance matrix with each entry corresponding to the similarity between a sentence pair. The distance matrix can be represented with a gray-scale image. Thus, a text segmentation problem is converted into an image segmentation problem. We apply the anisotropic diffusion technique to the image representation of the distance matrix to enhance the semantic cohesion of sentence topical groups as well as sharpen topical boundaries. At last, the dynamic programming technique is adapted to find the optimal topical boundaries and provide a zoom-in and zoom-out mechanism for topics access by segmenting text in variable numbers of sentence topical groups. Our approach involves no domain-specific training, and it can be applied to texts in a variety of domains. The experimental results show that our approach is effective in text segmentation and outperforms several state-of-the-art methods.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128813661","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: 69
Probabilistic term variant generator for biomedical terms 生物医学术语的概率术语变体生成器
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval Pub Date : 2003-07-28 DOI: 10.1145/860435.860467
Yoshimasa Tsuruoka, Junichi Tsujii
{"title":"Probabilistic term variant generator for biomedical terms","authors":"Yoshimasa Tsuruoka, Junichi Tsujii","doi":"10.1145/860435.860467","DOIUrl":"https://doi.org/10.1145/860435.860467","url":null,"abstract":"This paper presents an algorithm to generate possible variants for biomedical terms. The algorithm gives each variant its generation probability representing its plausibility, which is potentially useful for query and dictionary expansions. The probabilistic rules for generating variants are automatically learned from raw texts using an existing abbreviation extraction technique. Our method, therefore, requires no linguistic knowledge or labor-intensive natural language resource. We conducted an experiment using 83,142 MEDLINE abstracts for rule induction and 18,930 abstracts for testing. The results indicate that our method will significantly increase the number of retrieved documents for long biomedical terms.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125409189","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: 32
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