AbstractWe review the major paradigms for approximate similarity queries and propose a classification schema that easily allows existing approaches to be compared along several independent coordinates. Then, we discuss the impact that scheduling of index nodes can have on performance and show that, unlike exact similarity queries, no provable optimal scheduling strategy exists for approximate queries. On the positive side, we show that optimal-on-the-average schedules are well-defined and that their performance is indeed the best among practical schedules
Abstract. The indexing algorithms and data structures for similarity searching in metric spaces seem...
Abstract—We consider the problem of finding similar patterns in a time sequence. Typical application...
This paper proposes new solutions for the approximate dictionary queries problem. These solutions co...
In this article, we review the major paradigms for approximate similarity queries and propose a cla...
We review the major paradigms for approximate similarity queries and propose a classification schema...
Edit distance similarity search, also called approximate pattern matching, is a fundamental problem ...
Search engines and recommendation systems are built to efficiently display relevant information from...
Approximate query processing based on multiple similarity metrics is prevalent and essential for man...
Similarity search based on a distance function in metric spaces is a fundamental problem for many ap...
Approximate similarity queries are a practical way to obtain good, yet suboptimal, results from larg...
Similarity search has become one of the important parts of many applications including multimedia re...
AbstractWe present a radically new indexing approach for approximate string matching. The scheme use...
Metric databases are databases where a metric distance function is defined for pairs of database obj...
In this thesis, we study high dimensional approximate similarity search algorithms. High dimensional...
Abstract. Similarity queries searching for the most similar objects in a database compared to a give...
Abstract. The indexing algorithms and data structures for similarity searching in metric spaces seem...
Abstract—We consider the problem of finding similar patterns in a time sequence. Typical application...
This paper proposes new solutions for the approximate dictionary queries problem. These solutions co...
In this article, we review the major paradigms for approximate similarity queries and propose a cla...
We review the major paradigms for approximate similarity queries and propose a classification schema...
Edit distance similarity search, also called approximate pattern matching, is a fundamental problem ...
Search engines and recommendation systems are built to efficiently display relevant information from...
Approximate query processing based on multiple similarity metrics is prevalent and essential for man...
Similarity search based on a distance function in metric spaces is a fundamental problem for many ap...
Approximate similarity queries are a practical way to obtain good, yet suboptimal, results from larg...
Similarity search has become one of the important parts of many applications including multimedia re...
AbstractWe present a radically new indexing approach for approximate string matching. The scheme use...
Metric databases are databases where a metric distance function is defined for pairs of database obj...
In this thesis, we study high dimensional approximate similarity search algorithms. High dimensional...
Abstract. Similarity queries searching for the most similar objects in a database compared to a give...
Abstract. The indexing algorithms and data structures for similarity searching in metric spaces seem...
Abstract—We consider the problem of finding similar patterns in a time sequence. Typical application...
This paper proposes new solutions for the approximate dictionary queries problem. These solutions co...