RIAO Conference最新文献_第10页

Optimizations of Local Edition for Evaluating Similarity Between Monophonic Musical Sequences 评价单音音乐序列相似性的局部版本优化

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931397

P. Hanna, Pascal Ferraro

引用次数: 20

Evaluating A Personal Information Assistant 评估个人信息助理

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931417

J. Psarras, J. Jose

引用次数: 2

Smart Qualitative Data (SQUAD): Information Extraction in a Large Document Archive 智能定性数据(SQUAD):大型文档档案中的信息提取

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931452

Maria Milosavljevic, Claire Grover, Louise Corti

引用次数: 7

Extracting Useful Information from the Full Text of Fiction 从小说全文中提取有用信息

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931450

Sharon Givon, Maria Milosavljevic

引用次数: 0

Effectiveness of Rich Document Representation in XML Retrieval 富文档表示在XML检索中的有效性

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931413

F. Raja, Mostafa Keikha, M. Rahgozar, F. Oroumchian

{"title":"Effectiveness of Rich Document Representation in XML Retrieval","authors":"F. Raja, Mostafa Keikha, M. Rahgozar, F. Oroumchian","doi":"10.5555/1931390.1931413","DOIUrl":"https://doi.org/10.5555/1931390.1931413","url":null,"abstract":"Information Retrieval (IR) systems are built with different goals in mind. Some IR systems target high precision that is to have more relevant documents on the first page of their results. Other systems may target high recall that is finding as many references as possible. In this paper we present a method of document representation called RDR to build XML retrieval engines with high specificity; that is finding more relevant documents that are mostly about the query topic. The Rich Document Representation (RDR) is a method of representing the content of a document with logical terms and statements. The conjecture is that since RDR is a better representation of the document content it will produce higher precision. In our implementation, we used the Vector Space model to compute the similarity between the XML elements and queries. Our experiments are conducted on INEX 2004 test collection. The results indicate that the use of richer features such as logical terms or statements for XML retrieval tends to produce more focused retrieval. Therefore it is a suitable document representation when users need only a few more specific references and are more interested in precision than recall.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133974196","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: 2

Estimating Importance Features for Fact Mining (With a Case Study in Biography Mining) 估算事实挖掘的重要特征(以传记挖掘为例)

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931464

S. F. Adafre, M. de Rijke

引用次数: 4

Capturing Sentence Prior for Query-Based Multi-Document Summarization 基于查询的多文档摘要的句子先验捕获

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931465

Jagadeesh Jagarlamudi, Prasad Pingali, Vasudeva Varma

{"title":"Capturing Sentence Prior for Query-Based Multi-Document Summarization","authors":"Jagadeesh Jagarlamudi, Prasad Pingali, Vasudeva Varma","doi":"10.5555/1931390.1931465","DOIUrl":"https://doi.org/10.5555/1931390.1931465","url":null,"abstract":"In this paper, we have considered a real world information synthesis task, generation of a fixed length multi document summary which satisfies a specific information need. This task was mapped to a topic-oriented, informative multi-document summarization. We also tried to estimate, given the human written reference summaries and the document set, the maximum performance (ROUGE scores) that can be achieved by an extraction-based summarization technique. Motivated by the observation that the current approaches are far behind the estimated maximum performance, we have looked at Information Retrieval techniques to improve the relevance scoring of sentences towards information need. Following information theoretic approach we have identified a measure to capture the notion of importance or prior of a sentence. Following a different decomposition of Probability Ranking Principle, the calculated importance/prior is incorporated into the final sentence scoring by weighted linear combination. In order to evaluate the performance, we have explored information sources like WWW and encyclopedia in computing the information measure in a set of different experiments. The t-test analysis of the improvement on DUC 2005 data set is found to be significant (p ~ 0.05). The same system has outperformed rest of the systems at DUC 2006 challenge in terms of ROUGE scores with a significant margin over the next best system.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126205956","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

Construction of a Vietnamese Corpora for Named Entity Recognition 越南语命名实体识别语料库的构建

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931459

ThaoPham Thi Xuan, Ai Kawazoe, Dinh Dien, Nigel Collier, Tran Quoc Tri

引用次数: 8

Using Markov Chains to Exploit Word Relationships in Information Retrieval 利用马尔可夫链挖掘信息检索中的词关系

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931428

Guihong Cao, Jian-Yun Nie, Jing Bai

引用次数: 14

Selecting Automatically the Best Query Translations 自动选择最佳查询翻译

RIAO Conference Pub Date : 2007-05-30 DOI: 10.5555/1931390.1931419

Pierre-Yves Berger, J. Savoy

{"title":"Selecting Automatically the Best Query Translations","authors":"Pierre-Yves Berger, J. Savoy","doi":"10.5555/1931390.1931419","DOIUrl":"https://doi.org/10.5555/1931390.1931419","url":null,"abstract":"In order to search corpora written in two or more languages, the simplest and most efficient approach is to translate the query submitted into the required language(s). To achieve this goal, we developed an IR model based on translation tools freely available on the Web (bilingual machine-readable dictionaries, machine translation systems). When comparing the retrieval effectiveness of manually and automatically translated queries, we found that manual translation outperformed machine-based approaches, yet performance differences varied from one language to the text. Moreover, when analyzing query-by-query performances, we found that query performances based on machine-based translations varied a great deal. We then wondered whether or not we could predict the retrieval performance of a translated query and apply this knowledge to select the best translation(s). To do so we designed and evaluated a predictive system based on logistic regression and then used it to select the top most appropriate machine-based translations. Using a set of 99 queries and a documents collection available in the German and Spanish languages (extracted from the CLEF-2001 and 2002 test suites), we show that the retrieval performance of the suggested query translation selection procedure is statistically better than the single best MT system, but still inferior to the retrieval performances resulting from manual translations.","PeriodicalId":120472,"journal":{"name":"RIAO Conference","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126656904","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: 6