Jaap Kamps

A Hybrid Approach to Domain-Specific Entity Linking

2015 · arXiv (Cornell University)

The current state-of-the-art Entity Linking (EL) systems are geared towards corpora that are as heterogeneous as the Web, and therefore perform sub-optimally on domain-specific corpora. A key open problem is how to construct effective EL …

Avoiding Your Teacher's Mistakes: Training Neural Networks with Controlled Weak Supervision

2017 · arXiv (Cornell University)

Training deep neural networks requires massive amounts of training data, but for many tasks only limited labeled data is available. This makes weak supervision attractive, using weak or noisy signals like the output of heuristic …

Impact of Tokenization, Pretraining Task, and Transformer Depth on Text Ranking

2021 · UvA-DARE (University of Amsterdam)

This paper documents the University of Amsterdam’s participation in the TREC 2020 Deep Learning Track. Rather than motivated by engineering the best scoring system, our work is motivated by our interest in analysis, informing our …

Where to Go on Your Next Trip?

2015

Recommendation based on user preferences is a common task for e-commerce websites. New recommendation algorithms are often evaluated by offline comparison to baseline algorithms such as recommending random or the most popular items. Here, we …

Neural Coreference Resolution for Dutch Parliamentary Documents with the DutchParliament Dataset

2023 · Data

The task of coreference resolution concerns the clustering of words and phrases referring to the same entity in text, either in the same document or across multiple documents. The task is challenging, as it concerns …

Neural Ranking Models with Weak Supervision

2017

Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of …

From Neural Re-Ranking to Neural Ranking

2018

The availability of massive data and computing power allowing for effective data driven neural approaches is having a major impact on machine learning and information retrieval research, but these models have a basic problem with …