Introducing MathQA -- A Math-Aware Question Answering System
June 28, 2019 Β· Declared Dead Β· π Information Discovery and Delivery
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Moritz Schubotz, Philipp Scharpf, Kaushal Dudhat, Yash Nagar, Felix Hamborg, Bela Gipp
arXiv ID
1907.01642
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL,
cs.DL
Citations
32
Venue
Information Discovery and Delivery
Last Checked
4 months ago
Abstract
We present an open source math-aware Question Answering System based on Ask Platypus. Our system returns as a single mathematical formula for a natural language question in English or Hindi. This formulae originate from the knowledge-base Wikidata. We translate these formulae to computable data by integrating the calculation engine sympy into our system. This way, users can enter numeric values for the variables occurring in the formula. Moreover, the system loads numeric values for constants occurring in the formula from Wikidata. In a user study, our system outperformed a commercial computational mathematical knowledge engine by 13%. However, the performance of our system heavily depends on the size and quality of the formula data available in Wikidata. Since only a few items in Wikidata contained formulae when we started the project, we facilitated the import process by suggesting formula edits to Wikidata editors. With the simple heuristic that the first formula is significant for the article, 80% of the suggestions were correct.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Information Retrieval
R.I.P.
π»
Ghosted
π
π
Old Age
Neural Graph Collaborative Filtering
R.I.P.
π»
Ghosted
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
R.I.P.
π»
Ghosted
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
R.I.P.
π
404 Not Found
Graph Neural Networks for Social Recommendation
R.I.P.
π»
Ghosted
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted