Add to ORKGAbstract: We discuss several approaches to similarity preserving coding of symbol sequences and possible connections of their distributed versions to metric embeddings. Interpreting sequence representation methods with embeddings can help develop an approach to their analysis and may lead to discovering useful properties
Abstract. The need to measure sequence similarity arises in many applicitation domains and often coi...
Efficient and expressive comparison of sequences is an essential procedure for learning with se-quen...
DNA Sequence Compression can be achieved through exploiting the intra-sequence and inter-sequence si...
We discuss several approaches to similarity preserving coding of symbol sequences and possible conne...
The minimal-length encoding approach is applied to define concept of sequence similarity. A sequence...
Similarity search in sequence databases is ofparamount importance in bioinformatics research. As the...
String kernel-based machine learning methods have yielded great success in practical tasks of struct...
A growing number of measures of sequence similarity is being based on some underlying notion of rela...
This paper introduces the sequence covering similarity, that we formally define for evaluating the s...
Sequence analysis has been an increasingly popular tool to find patterns in sociological sequences. ...
Over the last decades, sequence analysis has developed from a fiercely debated trick from computatio...
This article reviews objections to optimal-matching (OM) algorithms in sequence analysis and reformu...
) C. Faloutsos , H. V. Jagadish AT&T Bell Labs Murray Hill, NJ 07974 fchristos,jagg@research...
We analyze an approach to a similarity preserving coding of symbol sequences based on neural distrib...
We study the problem of similarity detection by sequence alignment with gaps, using a recently estab...
Abstract. The need to measure sequence similarity arises in many applicitation domains and often coi...
Efficient and expressive comparison of sequences is an essential procedure for learning with se-quen...
DNA Sequence Compression can be achieved through exploiting the intra-sequence and inter-sequence si...
We discuss several approaches to similarity preserving coding of symbol sequences and possible conne...
The minimal-length encoding approach is applied to define concept of sequence similarity. A sequence...
Similarity search in sequence databases is ofparamount importance in bioinformatics research. As the...
String kernel-based machine learning methods have yielded great success in practical tasks of struct...
A growing number of measures of sequence similarity is being based on some underlying notion of rela...
This paper introduces the sequence covering similarity, that we formally define for evaluating the s...
Sequence analysis has been an increasingly popular tool to find patterns in sociological sequences. ...
Over the last decades, sequence analysis has developed from a fiercely debated trick from computatio...
This article reviews objections to optimal-matching (OM) algorithms in sequence analysis and reformu...
) C. Faloutsos , H. V. Jagadish AT&T Bell Labs Murray Hill, NJ 07974 fchristos,jagg@research...
We analyze an approach to a similarity preserving coding of symbol sequences based on neural distrib...
We study the problem of similarity detection by sequence alignment with gaps, using a recently estab...
Abstract. The need to measure sequence similarity arises in many applicitation domains and often coi...
Efficient and expressive comparison of sequences is an essential procedure for learning with se-quen...
DNA Sequence Compression can be achieved through exploiting the intra-sequence and inter-sequence si...