Proceedings of the 21st Australasian Document Computing Symposium最新文献

Boosting Titles does not Generally Improve Retrieval Effectiveness 增强标题通常不能提高检索效率

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015028

Jimmy, G. Zuccon, B. Koopman

引用次数: 8

Interactive Trip Planning Using Activity Trajectories 使用活动轨迹的交互式旅行计划

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015030

Sheng Wang, Z. Bao, J. Culpepper, T. Sellis, M. Sanderson, Munkh-Erdene Yadamjav

{"title":"Interactive Trip Planning Using Activity Trajectories","authors":"Sheng Wang, Z. Bao, J. Culpepper, T. Sellis, M. Sanderson, Munkh-Erdene Yadamjav","doi":"10.1145/3015022.3015030","DOIUrl":"https://doi.org/10.1145/3015022.3015030","url":null,"abstract":"We present an interactive trip planning system called @FINDER which uses an exemplar trajectory query to find the most related top-k spatial-textual trajectories. @FINDER is implemented to support various degrees of user information needs for trip planning. For users with zero knowledge about places to travel, @FINDER provides a heatmap of popular points of interest (POIs) as well as popular activities from a trajectory database. The system helps users quickly explore the places, and helps formulate an exemplar trajectory query, which specifies preferred places to go and activities of interest. Then @FINDER provides efficient query processing of the top-k related spatial-textual trajectories using a new approach to spatial-textual trajectory indexing recently developed at RMIT University. For each of the top-k results found in the form of a set of POIs and activities, @FINDER further computes the optimal route (in term of the travel time) covering all of the POIs, and returns an album to the user. Lastly, users can further interact with @FINDER by adding or deleting POIs/activities in the original exemplar query, and the system will update the results in a timely manner.","PeriodicalId":334601,"journal":{"name":"Proceedings of the 21st Australasian Document Computing Symposium","volume":"288 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133678259","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: 4

Effective User Relevance Feedback for Image Retrieval with Image Signatures 基于图像签名的有效用户相关反馈图像检索

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015034

Dinesha Chathurani Nanayakkara Wasam Uluwitige, S. Geva, G. Zuccon, V. Chandran, Timothy Chappell

{"title":"Effective User Relevance Feedback for Image Retrieval with Image Signatures","authors":"Dinesha Chathurani Nanayakkara Wasam Uluwitige, S. Geva, G. Zuccon, V. Chandran, Timothy Chappell","doi":"10.1145/3015022.3015034","DOIUrl":"https://doi.org/10.1145/3015022.3015034","url":null,"abstract":"Content-based image retrieval (CBIR) has attracted much attention due to the exponential growth of digital image collections that have become available in recent years. Relevance feedback (RF) in the context of search engines is a query expansion technique, which is based on relevance judgments about the top results that are initially returned for a given query. RF can be obtained directly from end users, inferred indirectly from user interactions with a result list, or even assumed (aka pseudo relevance feedback). RF information is used to generate a new query, aiming to re-focus the query towards more relevant results. This paper presents a methodology for use of signature based image retrieval with a user in the loop to improve retrieval performance. The significance of this study is twofold. First, it shows how to effectively use explicit RF with signature based image retrieval to improve retrieval quality and efficiency. Second, this approach provides a mechanism for end users to refine their image queries. This is an important contribution because, to date, there is no effective way to reformulate an image query; our approach provides a solution to this problem. Empirical experiments have been carried out to study the behaviour and optimal parameter settings of this approach. Empirical evaluations based on standard benchmarks demonstrate the effectiveness of the proposed approach in improving the performance of CBIR in terms of recall, precision, speed and scalability.","PeriodicalId":334601,"journal":{"name":"Proceedings of the 21st Australasian Document Computing Symposium","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128501703","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

Using Semantic and Context Features for Answer Summary Extraction 基于语义和上下文特征的答案摘要提取

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015031

E. Yulianti, Ruey-Cheng Chen, Falk Scholer, M. Sanderson

引用次数: 9

In Vacuo and In Situ Evaluation of SIMD Codecs SIMD编解码器的真空和原位评价

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015023

A. Trotman, Jimmy J. Lin

引用次数: 10

Proceedings of the 21st Australasian Document Computing Symposium 第21届澳洲文献计算研讨会论文集

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022

Sarvnaz Karimi, Mark James Carman

引用次数: 1

Occupational Representativeness in Twitter 推特的职业代表性

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015036

S. Kim, Stephen Wan, Cécile Paris

引用次数: 3

Query-Biased Summaries for Tabular Data 表格数据的查询偏置摘要

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015027

Vincent Au, Paul Thomas, Gaya K. Jayasinghe

引用次数: 2

Uncertainty in Rank-Biased Precision 秩偏精度中的不确定性

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015029

L. Park

引用次数: 2

Dynamic Cutoff Prediction in Multi-Stage Retrieval Systems 多级检索系统的动态截止预测

Proceedings of the 21st Australasian Document Computing Symposium Pub Date : 2016-12-05 DOI: 10.1145/3015022.3015026

J. Culpepper, C. Clarke, Jimmy J. Lin

{"title":"Dynamic Cutoff Prediction in Multi-Stage Retrieval Systems","authors":"J. Culpepper, C. Clarke, Jimmy J. Lin","doi":"10.1145/3015022.3015026","DOIUrl":"https://doi.org/10.1145/3015022.3015026","url":null,"abstract":"Modern multi-stage retrieval systems are comprised of a candidate generation stage followed by one or more reranking stages. In such an architecture, the quality of the final ranked list may not be sensitive to the quality of the initial candidate pool, especially in terms of early precision. This provides several opportunities to increase retrieval efficiency without significantly sacrificing effectiveness. In this paper, we explore a new approach to dynamically predicting the size of an initial result set in the candidate generation stage, which can directly affect the overall efficiency and effectiveness of the entire system. Previous work exploring this tradeoff has focused on global parameter settings that apply to all queries, even though optimal settings vary across queries. In contrast, we propose a technique that makes a parameter prediction to maximize efficiency within an effectiveness envelope on a per query basis, using only static pre-retrieval features. Experimental results show that substantial efficiency gains are achievable. In addition, our framework provides a versatile tool that can be used to estimate the effectiveness-efficiency tradeoffs that are possible before selecting and tuning algorithms to make machine-learned predictions.","PeriodicalId":334601,"journal":{"name":"Proceedings of the 21st Australasian Document Computing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130901652","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