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Showing 1 to 20 of 60 for “"Similarity search"”.
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Efficient Similarity Search in Structured Data
… for solving those problems are based on similarity search in databases. This makes efficient similarity search in large databases of structured objects an important basic operation for modern database applications. In this thesis we develop efficient methods for similarity search in large …
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Private Similarity Search with Sublinear Communication
Nearest neighbor search is a fundamental building-block for a wide range of applications. A privacy-preserving protocol for nearest neighbor search involves a set of clients who send queries to a remote database. Each client retrieves the nearest neighbor(s) to its query in the database without …
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Code Similarity Search in a Latent Space
… of program source codes that supports fast search via code similarity would be useful for several applications, including automated program synthesis and debugging, and user-facing code search in an integrated development environment. Here, "similar" is defined with respect to a set of …
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Effective and efficient similarity search in databases
… set of records in a database and a query record, similarity search aims to find all records sufficiently similar to the query record. To solve this problem, two main aspects need to be considered: First, to perform effective search, the set of relevant records is defined using a similarity …
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Efficient similarity search in high-dimensional data spaces
Similarity search in high-dimensional data spaces is a popular paradigm for many modern database applications, such as content based image retrieval, time series analysis in financial and marketing databases, and data mining. Objects are represented as high-dimensional points or vectors based on …
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Hash code learning for large scale similarity search
… distance calculations to approximate pairwise similarity. This graph can be used in various unsupervised hashing methods which require a similarity matrix. Current unsupervised image graph construction methods are dominated by those which utilize the manifold structure of images in the feature …
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Improving Profile Similarity Search and Alignment of Protein Sequences
… sites. Current sequence-based homology search methods are still unable to detect many similarities evident from protein spatial structures. We present a new method, COMPADRE, to assess the relationship between the query sequence and a hit in the database by considering the similarity …
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Learning compact hashing codes for large-scale similarity search
… representations for efficient storage and fast search becomes increasingly important. Moreover, these representations should preserve similarity, i.e., similar objects should have similar representations. Hashing algorithms, which encode objects into compact binary codes to preserve similarity, …
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High-dimensional similarity search and sketching : algorithms and hardness
… datasets: approximate near neighbor search (ANN) and sketching. We obtain a number of new results including: ' An algorithm for the ANN problem over the ℓ₁ and ℓ₂ distances that, for the first time, improves upon the Locality-Sensitive Hashing (LSH) framework. The key new insight is …
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Combining fast search and learning for scalable similarity search
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Mining, Indexing and Similarity Search in Large Graph Data Sets
… structural pattern discovery, interpretation and search. The formulation of a general graph information system through this study could provide fundamental supports to graph-intensive applications in multiple domains.
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Generative models meet similarity search: efficient, heuristic-free and robust retrieval
… to the problem of finding similar data. Exact similarity search, which aims to exhaustively find all relevant items through a linear scan in a dataset, is impractical due to its high computational complexity. Approximate-nearest-neighbor (ANN) search methods, especially the Learning-to-hash or …
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Design and analysis of algorithms for similarity search based on intrinsic dimension
… analysis, and anomaly detection, is that of similarity search. It has been used in numerous fields of application such as multimedia, information retrieval, recommender systems and pattern recognition. Specifically, a similarity query aims to retrieve from the database the most similar …
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G-hash: Towards Fast Kernel-based Similarity Search in Large Graph Databases
… including efficient storage, indexing, and similarity search. With the fast accumulation of graph databases, similarity search in graph databases has emerged as an important research topic. Graph similarity search has applications in a wide range of domains including chemoinformatics, …
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Learning compact hashing codes with complex objectives from multiple sources for large scale similarity search
<p>Similarity search is a key problem in many real world applications including image and text retrieval, content reuse detection and collaborative filtering. The purpose of similarity search is to identify similar data examples given a query example. Due to the explosive growth of the Internet, a …
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Real-time and retrospective discovery, anomaly detection, classification, and similarity search of supernovae in time-domain surveys and data streams
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01
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AsymSim: meta path-based similarity with asymmetric relations
Peer similarity search is a deceptively complex problem in information network analysis. Past research has primarily focused on similarity search in homogeneous networks, but real world data is often best represented using heterogeneous information networks, with multiple node and relation types …
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Community Classification of the Protein Universe
… performed by the community of protein sequence similarity search users. In the first chapter, I review the history of protein sequence and protein family databases, and how the abstract concept of a protein family is expressed as a computational model. I review in greater detail the protein …
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