Search Results for author: Anca Dumitrache

Found 8 papers, 6 papers with code

SemEval-2021 Task 12: Learning with Disagreements

no code implementations SEMEVAL 2021 Alexandra Uma, Tommaso Fornaciari, Anca Dumitrache, Tristan Miller, Jon Chamberlain, Barbara Plank, Edwin Simpson, Massimo Poesio

Disagreement between coders is ubiquitous in virtually all datasets annotated with human judgements in both natural language processing and computer vision.

Beyond Optimizing for Clicks: Incorporating Editorial Values in News Recommendation

no code implementations21 Apr 2020 Feng Lu, Anca Dumitrache, David Graus

In our first study we explore how our news recommender steers reading behavior in the context of editorial values such as serendipity, dynamism, diversity, and coverage.

News Recommendation Recommendation Systems +1

A Crowdsourced Frame Disambiguation Corpus with Ambiguity

1 code implementation NAACL 2019 Anca Dumitrache, Lora Aroyo, Chris Welty

We present a resource for the task of FrameNet semantic frame disambiguation of over 5, 000 word-sentence pairs from the Wikipedia corpus.


Crowdsourcing Semantic Label Propagation in Relation Classification

1 code implementation WS 2018 Anca Dumitrache, Lora Aroyo, Chris Welty

Distant supervision is a popular method for performing relation extraction from text that is known to produce noisy labels.

Classification General Classification +1

CrowdTruth 2.0: Quality Metrics for Crowdsourcing with Disagreement

2 code implementations18 Aug 2018 Anca Dumitrache, Oana Inel, Lora Aroyo, Benjamin Timmermans, Chris Welty

However, in many domains, there is ambiguity in the data, as well as a multitude of perspectives of the information examples.

Human-Computer Interaction Social and Information Networks

Capturing Ambiguity in Crowdsourcing Frame Disambiguation

1 code implementation1 May 2018 Anca Dumitrache, Lora Aroyo, Chris Welty

FrameNet is a computational linguistics resource composed of semantic frames, high-level concepts that represent the meanings of words.

False Positive and Cross-relation Signals in Distant Supervision Data

1 code implementation14 Nov 2017 Anca Dumitrache, Lora Aroyo, Chris Welty

Distant supervision (DS) is a well-established method for relation extraction from text, based on the assumption that when a knowledge-base contains a relation between a term pair, then sentences that contain that pair are likely to express the relation.

General Classification Relation Classification

Crowdsourcing Ground Truth for Medical Relation Extraction

1 code implementation9 Jan 2017 Anca Dumitrache, Lora Aroyo, Chris Welty

Cognitive computing systems require human labeled data for evaluation, and often for training.

Medical Relation Extraction Relation Extraction

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