Effectively and efficiently supporting crowd-enabled databases via NoSQL paradigms
In this paper we provide an overview of the Hints From the Crowd (HFC) project, whose main goal is to build a NoSQL database system for large collections of product reviews; the database is queried by expressing a natural language sentence; the result is a list of products ranked based on the relevance of reviews w.r.t. the natural language sentence. The best ranked products in the result list can be seen as the best hints for the user based on crowd opinions (the reviews). The HFC prototype has been developed as a web application, independent of the particular application domain of the collected product reviews. Queries are performed by evaluating a text-based ranking metric for sets of re…
The Hints from the Crowd Project
Can the crowd be a source of information? Is it possible to receive useful hints from comments, blogs and product reviews? In the era of Web 2.0, people are allowed to give their opinion about everything such as movies, hotels, etc.. These reviews are social knowledge, that can be exploited to suggest possibly interesting items to other people. The goal of the Hints From the Crowd HFC project is to build a NoSQL database system for large collections of product reviews; the database is queried by expressing a natural language sentence; the result is a list of products ranked based on the relevance of reviews w.r.t. the natural language sentence. The best ranked products in the result list ca…
Querying NoSQL-based crowdsourcing systems efficiently
In this paper, we provide a novel approach for effectively and efficiently support query processing tasks in novel NoSQL crowdsourcing systems. The idea of our method is to exploit the social knowledge available from reviews about products of any kind, freely provided by customers through specialized web sites. We thus define a NoSQL database system for large collections of product reviews, where queries can be expressed in terms of natural language sentences whose answers are modeled as lists of products ranked based on the relevance of reviews w.r.t. the natural language sentences. The best ranked products in the result list can be seen as the best hints for the user based on crowd opinio…
Hints from the Crowd: A Novel NoSQL Database
The crowd can be an incredible source of information. In particular, this is true for reviews about products of any kind, freely provided by customers through specialized web sites. In other words, they are social knowledge, that can be exploited by other customers. The Hints From the Crowd HFC prototype, presented in this paper, is a NoSQL database system for large collections of product reviews; the database is queried by expressing a natural language sentence; the result is a list of products ranked based on the relevance of reviews w.r.t. the natural language sentence. The best ranked products in the result list can be seen as the best hints for the user based on crowd opinions the revi…
Enhanced query processing for NoSQL crowdsourcing systems
In this paper, we provide a novel approach for effectively and efficiently support query processing tasks in novel NoSQL crowdsourcing systems. The idea of our method is to exploit the social knowledge available from reviews about products of any kind, freely provided by customers through specialized web sites. We thus define a NoSQL database system for large collections of product reviews, where queries can be expressed in terms of natural language sentences whose answers are modeled as lists of products ranked based on the relevance of reviews w.r.t. the natural language sentences. The best ranked products in the result list can be seen as the best hints for the user based on crowd opinio…