Uniform definition of comparable and searchable information on the web

TL;DR

This paper introduces 'Domain Spaces' and 'Domain Vectors' as a unified, online framework for defining, searching, and comparing precise, objectifiable information on the web using ordered, metric spaces and numeric sequences.

Contribution

It proposes a novel online system for defining and searching comparable information using nestable metric spaces called Domain Spaces and Domain Vectors, enhancing objectivity and searchability.

Findings

Demonstrated in an online database with a search engine

Enables uniform, comparable, and searchable numeric data

Improves objectivity and efficiency in information retrieval

Abstract

Basically information means selection within a domain (value or definition set) of possibilities. For objectifiable, comparable and precise information the domain should be the same for all. Therefore the global (online) definition of the domain is proposed here. It is advantageous to define an ordered domain, because this allows using numbers for addressing the elements and because nature is ordered in many respects. The original data can be ordered in multiple independent ways. We can define a domain with multiple independent numeric dimensions to reflect this. Because we want to search information in the domain, for quantification of similarity we define a distance function or metric. Therefore we propose "Domain Spaces" (DSs) which are online defined nestable metric spaces. Their elements are called "Domain Vectors" (DVs) and have the simple form: URL (of common DS definition) plus sequence of numbers At this the sequence must be given so that the mapping of numbers to the DS dimensions is clear. By help of appropriate software DVs can be represented e.g. as words and numbers. Compared to words, however, DVs have (as original information) important objectifiable advantages (clear definition, objectivity, information content, range, resolution, efficiency, searchability). Using DSs users can define which information they make searchable and how it is searchable. DSs can be also used to make quantitative (numeric) data as uniform DVs interoperable, comparable and searchable. The approach is demonstrated in an online database with search engine (http://NumericSearch.com). The search procedure is called "Numeric Search". It consists of two systematic steps: 1. Selection of the appropriate DS e.g. by conventional word based search within the DS definitions. 2. Range and/or similarity search of DVs in the selected DS.