QONTEXT

Quantum Contextual Information Access and Retrieval

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 Obiettivo del progetto (Objective)

'The huge number and diversity of the users, the advertising products and services, the rapid growth of online resources have imposed new challenges to the conventional search. Queries are becoming even more broad and complex essentially due to context of the search process (e.g. the system, user, language, the word and action meaning, socio-psychological dimensions, interface and interaction methods). Over the past three decades, the research in IAR had led to various search engine models, such as vector space and probabilistic models. Unfortunately there has been no comprehensive investigation at the theoretical level for effectively integrating elements of context to create advanced search technology. The key issue preventing such research is a lack of a unified theoretical framework to seamlessly integrate the dimensions of context into the search engine models and into the evaluation protocols. This proposal is hinged on the belief that the dimensions of context can be naturally integrated into a generic and fundamental framework. To address the challenges of the dimensions of context in IAR this proposal shows a new vision of the IAR paradigm based on Quantum Theory (QT). This proposal starts from Van Rijsbergen’s seminal book. QT allows to measure relevance and context via projection, and probability of relevance via the trace, to logically reason through lattice of document structures and links, to change context via unitary operators, to handle correlations dependencies as density operators, to represent composite, entangled documents and features for which classical correlations cannot straightforwardly be used. The work independently done so far for some years by the partners suggest that more effective results can be obtained only if the expertises are exchanged through a network which would allow the partners to work together and exchange a wide range of expertises which is hardly possessed by a single team.'

Introduzione (Teaser)

Accessing and retrieving relevant information has grown along with an expanding knowledge economy. A new way of accessing and retrieving information based on quantum theory may help advance the growing need for quality data.

Descrizione progetto (Article)

An explosion of information on anything and everything, both online and offline, is posing challenges for citizens and researchers who want to home in on particular data that they are looking for. While research in Information Access and Retrieval (IAR) has come a long way in the last three decades, experts have not yet integrated elements of 'context' to yield more advanced search engines.

The EU-funded project 'Quantum contextual information access and retrieval' (http://qontext.dei.unipd.it/ (QONTEXT)) worked on creating better search engine technology by seamlessly integrating different dimensions of context into search engine models and evaluation protocols.

What the project team meant by context is the need to take into consideration within the search specific information about the user, as well as language, system, interface and interaction. It also wanted to integrate socio-psychological dimensions and other nuances about the search in order to yield better search and research results.

To achieve its aims, QONTEXT unveiled a new vision of the IAR paradigm based on quantum theory, which boasts many advantages in improving searches. Quantum theory is able to measure relevance and context more effectively. It is better at estimating the probability of relevance and to logically reason through documents and links. The concept is also ideal for understanding correlations and dependencies, as well as representing complex documents when classical correlations cannot deliver.

Integrating elements of context by exploiting quantum theory may help researchers and information seekers access and retrieve more useful and meaningful information than ever before.