A List by Author: Pavel Zezula
Employing Subsequence Matching in Audio Data Processing
We overview current problems of audio retrieval and time-series subsequence matching. We discuss the usage of subsequence matching approaches in audio data processing, especially in automatic speech recognition (ASR) area and we aim at improving performance of the retrieval process. To overcome the problems known from the time-series area like the occurrence of implementation bias and data bias we present a Subsequence Matching Framework as a tool for fast prototyping, building, and testing similarity search subsequence matching applications. The framework is build on top of MESSIF (Metric Similarity Search Implementation Framework) and thus the subsequence matching algorithms can exploit advanced similarity indexes in order to significantly increase their query processing performance. To prove our concept we provide a design of query-by-example spoken term detection type of application with the usage of phonetic posteriograms and subsequence matching approach.
Adaptive Approximate Similarity Searching through Metric Social Networks
Exploiting the concepts of social networking represents a novel approach to the approximate similarity query processing. We present an unstructured and dynamic P2P environment in which a metric social network is built. Social communities of peers giving similar results to specific queries are established and such ties are exploited for answering future queries. Based on the universal law of generalization, a new query forwarding algorithm is introduced and evaluated. The same principle is used to manage query histories of individual peers with the possibility to tune the tradeoff between the extent of the
LOBS: Load Balancing for Similarity Peer-to-Peer Structures
The real-life experience with the similarity search shows that this task is
rhoIndex, Designing and Evaluating an Indexing Structure for Graph Structured Data
An own design of an indexing structure for general graph structured data called rhoIndex that allows an effective processing of special path queries is presented. These special queries represent for example a search for all paths lying between two arbitrary vertices limited to a certain path length. The rhoIndex is a multilevel balanced tree structure where each node is created with a certain graph transformation and described by modified adjacency matrix. Hence, rhoIndex indexes all the paths to a predefined length linclusive. The search algorithm is then able to find all the paths shorter than or having the length land some of the paths longer then the predefined llying between any two vertices in the indexed graph. The designed search algorithm exploits a special graph structure, a transcription graph, to compute the result using the rhoIndex . We also present an experimental evaluation of the process of creating the rhoIndex on graphs with different sizes and also a complexity evaluation of the search algorithm that uses the rhoIndex.
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