Item Matching using Text Description and Similarity Search
June 28, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ana Paula Appel, Anderson Luis de Paula Silva, Adriana Reigota Silva, Caique Dutra Santos, Thiago Logo da Silva, Rafael Poggi de Araujo, Luiz Carlos Faray de Aquino
arXiv ID
2206.14097
Category
cs.IR: Information Retrieval
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In this paper, we focus on the problem of item matching using only the description. Those specific items not only lack a unique code but also contain short text descriptions, making the item matching process difficult. Our goal is to compare products using only the description provided by the purchase process. Therefore, evaluating other characteristics and differences can uncover possible flaws during the acquiring phase. However, the text of the items that we were working on was very small, with numbers due to the nature of the products and we have a limited amount of time to develop the solution which was 8 weeks. As result, we showed that working using a well-oriented methodology we were able to deliver a successful MVP and achieve the results expected with up to 55% match.
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