Hashing of databases based on indirect observations of Hamming distances

نویسنده

  • Vladimir B. Balakirsky
چکیده

We describe hashing of data bases as a problem of information and coding theory. It is shown that the triangle inequality for the Hamming distances between binary vectors may essentially decrease the computational eeorts of a search for a pattern in the data base. Introduction of the Lee distance in the space, which consists of the Hamming distances, leads to a new metric space where the triangle inequality can be eeectively used.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hashing of Databases with the Use of Metric Properties of the Hamming Space

Hashing of databases is considered from the point of view of information and coding theory. The records of a database are represented as binary vectors of the same length stored in the external memory of a computer. The task is formulated as follows: given a pattern and a fixed size of working memory, form the set of addresses of records that can disagree with the pattern in the number of posit...

متن کامل

Compressed Image Hashing using Minimum Magnitude CSLBP

Image hashing allows compression, enhancement or other signal processing operations on digital images which are usually acceptable manipulations. Whereas, cryptographic hash functions are very sensitive to even single bit changes in image. Image hashing is a sum of important quality features in quantized form. In this paper, we proposed a novel image hashing algorithm for authentication which i...

متن کامل

The Normalized Distance Preserving Binary Codes and Distance Table

In the Euclidean space, the approximate nearest neighbors (ANN) search measures the similarity degree through computing the Euclidean distances, which owns high time complexity and large memory overhead. To address these problems, this paper maps the data from the Euclidean space into the Hamming space, and the normalized distance similarity restriction and the quantization error are required t...

متن کامل

Learning to Hash with Binary Reconstructive Embeddings

Fast retrieval methods are increasingly critical for many large-scale analysis tasks, and there have been several recent methods that attempt to learn hash functions for fast and accurate nearest neighbor searches. In this paper, we develop an algorithm for learning hash functions based on explicitly minimizing the reconstruction error between the original distances and the Hamming distances of...

متن کامل

Capacity Inverse Minimum Cost Flow Problem under the Weighted Hamming Distances

Given an instance of the minimum cost flow problem, a version of the corresponding inverse problem, called the capacity inverse problem, is to modify the upper and lower bounds on arc flows as little as possible so that a given feasible flow becomes optimal to the modified minimum cost flow problem. The modifications can be measured by different distances. In this article, we consider the capac...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • IEEE Trans. Information Theory

دوره 42  شماره 

صفحات  -

تاریخ انتشار 1996