Pushing the boundaries of crowd-enabled databases with query-driven schema expansion

Selke, Joachim; Lofi, Christoph; Balke, Wolf‐Tilo

doi:10.14778/2168651.2168655

Cited by 32 publications

(13 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These platforms have successfully been used by researchers from many different domains and knowledge processing tasks, e.g., disaster response [4], providing training data for machinelearning-based approaches [5], or performing large scale user studies for evaluating new prototype implementations [6], or performing surveys with a large and diverse number of participants for investigating general human behavior or preferences [7].…”

Section: Crowdsourcingmentioning

confidence: 99%

Crowdsourcing for Query Processing onWeb Data: A Case Study on the Skyline Operator

Maarry

Lofi

Balke

2015

CIT

Self Cite

View full text Add to dashboard Cite

In recent years, crowdsourcing has become a powerful tool to bring human intelligence into information processing. This is especially important for Web data which in contrast to well-maintained databases is almost always incomplete and may be distributed over a variety of sources. Crowdsourcing allows to tackle many problems which are not yet attainable using machine-based algorithms alone: in particular, it allows to perform database operators on incomplete data as human workers can be used to provide values during runtime. As this can become costly quickly, elaborate optimization is required. In this paper, we showcase how such optimizations can be performed for the popular skyline operator for preference queries. We present some heuristics-based approaches and compare them to crowdsourcing-based approaches using sophisticated optimization techniques while especially focusing on result correctness.

show abstract

Section: Crowdsourcingmentioning

confidence: 99%

Crowdsourcing for Query Processing onWeb Data: A Case Study on the Skyline Operator

Maarry

Lofi

Balke

2015

CIT

Self Cite

View full text Add to dashboard Cite

show abstract

“…There exists equivalent works which consider a unified language, proposing some SQL extension [10,15,3,7,11], or consider a metamodel approache such as the Apache's MetaModel project 2 . To overcome existing problems of data integration, we propose a solution to exploit a crowd of experts in a transparent way.…”

Section: Related Workmentioning

confidence: 99%

“…We do not assume having a unified query language, but rather we follow the idea of the polyglot persistence movement to support multiple languages. The idea of using crowdsourcing for answering queries over a database has been covered in previous works [15,3,16,7,9,11,5]. In particular, CrowdDB [9] integrates human inputs within a query plan that contains operations that usual database systems cannot always answer correctly (i.e.…”

Section: Related Workmentioning

confidence: 99%

NoXperanto: Crowdsourced Polyglot Persistence

Maccioni¹,

Cassano²,

Luo³

et al. 2014

Polibits

View full text Add to dashboard Cite

This paper proposes NoXperanto, a novel crowdsourcing approach to address querying over data collections managed by polyglot persistence settings. The main contribution of NoXperanto is the ability to solve complex queries involving different data stores by exploiting queries from expert users (i.e. a crowd of database administrators, data engineers, domain experts, etc.), assuming that these users can submit meaningful queries. NoXperanto exploits the results of "meaningful queries" in order to facilitate the forthcoming query answering processes. In particular, queries results are used to: (i) help non-expert users in using the multi-database environment and (ii) improve performances of the multi-database environment, which not only uses disk and memory resources, but heavily rely on network bandwidth. NoXperanto employs a layer to keep track of the information produced by the crowd modeled as a Property Graph and managed in a Graph Database Management System (GDBMS).

show abstract

“…Crowdsoucing was also suggested as method for data cleaning, integration and analytics, entity resolution, schema expansion (e.g. [12], [24], [27], [16]). Crowdsourcing attracted also interest from the AI community with research aiming at dynamic workflow executions that optimally use the crowd for accomplishing a given complex task (e.g.…”

Section: Related Workmentioning

confidence: 99%

Answering planning queries with the crowd

et al. 2013

View full text Add to dashboard Cite

Recent research has shown that crowd sourcing can be used effectively to solve problems that are difficult for computers, e.g., optical character recognition and identification of the structural configuration of natural proteins. In this paper we propose to use the power of the crowd to address yet another difficult problem that frequently occurs in a daily life -answering planning queries whose output is a sequence of objects/actions, when the goal, i.e, the notion of "best output", is hard to formalize. For example, planning the sequence of places/attractions to visit in the course of a vacation, where the goal is to enjoy the resulting vacation the most, or planning the sequence of courses to take in an academic schedule planning, where the goal is to obtain solid knowledge of a given subject domain. Such goals may be easily understandable by humans, but hard or even impossible to formalize for a computer.We present a novel algorithm for efficiently harnessing the crowd to assist in answering such planning queries. The algorithm builds the desired plans incrementally, choosing at each step the 'best' questions so that the overall number of questions that need to be asked is minimized. We prove the algorithm to be optimal within its class and demonstrate experimentally its effectiveness and efficiency.

show abstract

Pushing the boundaries of crowd-enabled databases with query-driven schema expansion

Cited by 32 publications

References 26 publications

Crowdsourcing for Query Processing onWeb Data: A Case Study on the Skyline Operator

Crowdsourcing for Query Processing onWeb Data: A Case Study on the Skyline Operator

NoXperanto: Crowdsourced Polyglot Persistence

Answering planning queries with the crowd

Contact Info

Product

Resources

About