2009 Second International Workshop on Similarity Search and Applications最新文献_第2页

Parallel Dynamic Batch Loading in the M-tree m树中的并行动态批加载

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.27

Jakub Lokoč

引用次数: 5

Query Routing Mechanisms in Self-Organizing Search Systems 自组织搜索系统中的查询路由机制

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.13

Vlastislav Dohnal, J. Sedmidubský

引用次数: 7

Img(Rummager): An Interactive Content Based Image Retrieval System Img(Rummager):一个基于交互式内容的图像检索系统

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.16

S. Chatzichristofis, Y. Boutalis, M. Lux

引用次数: 57

Approximate Direct and Reverse Nearest Neighbor Queries, and the k-nearest Neighbor Graph 近似的直接和反向近邻查询，以及k近邻图

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.33

Karina Figueroa, Rodrigo Paredes

{"title":"Approximate Direct and Reverse Nearest Neighbor Queries, and the k-nearest Neighbor Graph","authors":"Karina Figueroa, Rodrigo Paredes","doi":"10.1109/SISAP.2009.33","DOIUrl":"https://doi.org/10.1109/SISAP.2009.33","url":null,"abstract":"Retrieving the emph{k-nearest neighbors} of a query object is a basic primitive in similarity searching. A related, far less explored primitive is to obtain the dataset elements which would have the query object within their own emph{k}-nearest neighbors, known as the emph{reverse k-nearest neighbor} query. We already have indices and algorithms to solve emph{k}-nearest neighbors queries in general metric spaces; yet, in many cases of practical interest they degenerate to sequential scanning. The naive algorithm for reverse emph{k}-nearest neighbor queries has quadratic complexity, because the emph{k}-nearest neighbors of all the dataset objects must be found; this is too expensive. Hence, when solving these primitives we can tolerate trading correctness in the solution for searching time. In this paper we propose an efficient approximate approach to solve these similarity queries with high retrieval rate. Then, we show how to use our approximate emph{k}-nearest neighbor queries to construct (an approximation of) the emph{k-nearest neighbor graph} when we have a fixed dataset. Finally, combining both primitives we show how to emph{dynamically maintain} the approximate emph{k}-nearest neighbor graph of the objects currently stored within the metric dataset, that is, considering both object insertions and deletions.","PeriodicalId":130242,"journal":{"name":"2009 Second International Workshop on Similarity Search and Applications","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128136415","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

Dynamic Spatial Approximation Trees for Massive Data 海量数据的动态空间逼近树

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.28

G. Navarro, Nora Reyes

引用次数: 38

Speeding Up Permutation Based Indexing with Indexing 用索引加速基于排列的索引

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.12

Karina Figueroa, K. Fredriksson

引用次数: 18

On the Effectiveness of Distances Measuring Protein Structure Similarity 距离测量蛋白质结构相似性的有效性研究

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.19

Jakub Galgonek, D. Hoksza

引用次数: 2

Structural Entropic Difference: A Bounded Distance Metric for Unordered Trees 结构熵差:无序树的有界距离度量

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.29

R. Connor, Fabio Simeoni, Michael Iakovos

引用次数: 2

Searching by Similarity and Classifying Images on a Very Large Scale 基于相似性的大尺度图像搜索与分类

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.10

Giuseppe Amato, P. Savino

{"title":"Searching by Similarity and Classifying Images on a Very Large Scale","authors":"Giuseppe Amato, P. Savino","doi":"10.1109/SISAP.2009.10","DOIUrl":"https://doi.org/10.1109/SISAP.2009.10","url":null,"abstract":"In the demonstration we will show a system for searching by similarity and automatically classifying images in a very large dataset. The demonstrated techniques are based on the use of the MI-File (Metric Inverted File) as the access method for executing similarity search efficiently. The MI-File is an access methods based on inverted files that relies on a space transformation that use the notion of perspective to decide about the similarity between two objects. More specifically, if two objects are close one to each other, also the view of the space from their position is similar. Leveraging on this space transformation, it is possible to use inverted file to execute approximate similarity search. In order to test the scalability of this access method, we inserted 106 millions images from the CoPhIR dataset and we created an on-line search engine that allows everybody to search in this dataset. In addition we also used this access methods to perform automatic classification on this very large image dataset. More specifically, we reformulated the classification problem, as resulting from the use of SVM with RBF kernel, as a complex approximate similarity search problem. In such a way, instead of comparing every single image against the classifier, the best images belonging to a class are directly obtained as the result of a complex approximate similarity search query.","PeriodicalId":130242,"journal":{"name":"2009 Second International Workshop on Similarity Search and Applications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134388430","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: 0

img(Anaktisi): A Web Content Based Image Retrieval System 一个基于Web内容的图像检索系统

2009 Second International Workshop on Similarity Search and Applications Pub Date : 2009-08-29 DOI: 10.1109/SISAP.2009.15

Konstantinos Zagoris, Savvas A. Chatzichristofis, Nikos Papamarkos, Yiannis S. Boutalis

引用次数: 29