Magnitude estimation is a psychophysical scaling technique for the measurement of sensation, where observers assign numbers to stimuli in response their perceived intensity. We investigate use magnitude judging relevance documents information retrieval evaluation, carrying out large-scale user study across 18 TREC topics and collecting over 50,000 judgments using crowdsourcing. Our analysis shows that can be reliably collected crowdsourcing, are competitive terms assessor cost, are, on...

Crowdsourcing has become a standard methodology to collect manually annotated data such as relevance judgments at scale. On crowdsourcing platforms like Amazon MTurk or FigureEight, crowd workers select tasks work on based different dimensions task reward and requester reputation. Requesters then receive the of who self-selected into completed them successfully. Several workers, however, preview tasks, begin working them, reaching varying stages completion without finally submitting their...

Crowdsourcing has become a standard methodology to collect manually annotated data such as relevance judgments at scale. On crowdsourcing platforms like Amazon MTurk or FigureEight, crowd workers select tasks work on based different dimensions task reward and requester reputation. Requesters then receive the of who self-selected into completed them successfully. Several workers, however, preview tasks, begin working them, reaching varying stages completion without finally submitting their...

In the context of micro-task crowdsourcing, each task is usually performed by several workers. This allows researchers to leverage measures agreement among workers on same task, estimate reliability collected data and better understand answering behaviors participants. While many between annotators have been proposed, they are known for suffering from problems abnormalities. this paper, we identify main limits existing in crowdsourcing context, both means toy examples as well with real-world...

Crowdsourcing has become an alternative approach to collect relevance judgments at scale thanks the availability of crowdsourcing platforms and quality control techniques that allow obtain reliable results. Previous work used ask multiple crowd workers judge a document with respect query studied how best aggregate same topic-document pair. This paper addresses aspect been rather overlooked so far: we study time available express judgment affects its quality. We also discuss loss making...

Crowdsourcing is a popular technique to collect large amounts of human-generated labels, such as relevance judgments used create information retrieval (IR) evaluation collections. Previous research has shown how collecting high quality labels from crowdsourcing platform can be challenging. Existing assurance techniques focus on answer aggregation or the use gold questions where ground-truth data allows check for responses.

Magnitude estimation is a psychophysical scaling technique for the measurement of sensation, where observers assign numbers to stimuli in response their perceived intensity. We investigate use magnitude judging relevance documents context information retrieval evaluation, carrying out large-scale user study across 18 TREC topics and collecting more than 50,000 judgments. Our analysis shows that on average judgments are rank-aligned with ordinal made by expert assessors. An advantage users...

In Information Retrieval evaluation, the classical approach of adopting binary relevance judgments has been replaced by multi-level and gain-based metrics leveraging such judgment scales. Recent work also proposed evaluated unbounded scales means Magnitude Estimation (ME) compared them with While ME brings advantages like ability for assessors to always judge next document as having higher or lower than any documents they have judged so far, it comes some drawbacks. For example, is not a...

The agreement between relevance assessors is an important but understudied topic in the Information Retrieval literature because of limited data available about documents assessed by multiple judges. This issue has gained even more importance recently light crowdsourced judgments, where it customary to gather many labels for each topic-document pair. In a crowdsourcing setting, often used as proxy quality, although without any systematic verification conjecture that higher corresponds...

Information Retrieval (IR) researchers have often used existing IR evaluation collections and transformed the relevance scale in which judgments been collected, e.g., to use metrics that assume binary like Mean Average Precision. Such transformations are arbitrary (e.g., 0,1 mapped 0 2,3 1) it is assumed they no impact on results of evaluation. Moreover, crowdsourcing collect has become a standard methodology. When designing judgment task, one decision be made how granular should be. then...

Crowdsourcing, i.e., the outsourcing of tasks typically performed by a few experts to large crowd as an open call, has been shown be reasonably effective in many cases, like Wikipedia, Chess match Kasparov against world 1999, and several others. The aim present paper is describe setup experimentation crowdsourcing techniques applied quantification immunohistochemistry. Fourteen Images from MIB1-stained breast specimens were first manually counted pathologist, then submitted platform through...

Microtask crowdsourcing platforms are social intelligence systems in which volunteers, called crowdworkers, complete small, repetitive tasks return for a small fee. Beyond payments, task requesters considering non-monetary incentives such as points, badges, and other gamified elements to increase performance improve crowdworker experience. In this article, we present Qrowdsmith, platform gamifying microtask crowdsourcing. To design the system, explore empirically range of financial analyse...

There is an important ongoing effort aimed to tackle misinformation and perform reliable fact-checking by employing human assessors at scale, with a crowdsourcing-based approach. Previous studies on the feasibility of crowdsourcing for task detection have provided inconsistent results: some them seem confirm effectiveness assessing truthfulness statements claims, whereas others fail reach level higher than automatic machine learning approaches, which are still unsatisfactory. In this paper,...

Crowdsourcing tasks have been widely used to collect a large number of human labels at scale. While some these are deployed by requesters and performed only once crowd workers, others require the same worker perform task or variant it more than once, thus participating in so-called longitudinal study . Despite prevalence studies crowdsourcing, there is limited understanding factors that influence participation them across different crowdsourcing marketplaces. We present results from...

We present the Virtual City Explorer (VCE), an online crowdsourcing platform for collection of rich geotagged information in urban environments. Compared to other volunteered geographic approaches, which are constrained by number and availability mapping enthusiasts on ground, VCE uses digital street imagery allow people virtually explore a city from anywhere world, using browser or mobile phone. In addition, contributions designed as paid microtasks—small jobs that can be carried out...

We investigate the problem of generating natural language summaries from knowledge base triples. Our approach is based on a pointer-generator network, which, in addition to regular words fixed target vocabulary, able verbalise triples several ways. undertake an automatic and human evaluation single open-domain generation tasks. Both show that our significantly outperforms other data-driven baselines.

Keyphrases are short phrases that best represent a document content. They can be useful in variety of applications, including summarization and retrieval models. In this paper, we introduce the first dataset keyphrases for an Arabic collection, obtained by means crowdsourcing. We experimentally evaluate different crowdsourced answer aggregation strategies validate their performances against expert annotations to quality our dataset. report about experimental results, features, some lessons...