20 citations · 61 across the 7 of their papers we have counts for
7 papers
A Survey on Automated Program Repair Techniques
Kai Huang, Zhengzi Xu, Su Yang +4
With the rapid development and large-scale popularity of program software, modern society increasingly relies on software systems. However, the problems exposed by software have al…
An Empirical Comparison of FAISS and FENSHSES for Nearest Neighbor Search in Hamming Space
Cun Mu, Binwei Yang, Zheng Yan
In this paper, we compare the performances of FAISS and FENSHSES on nearest neighbor search in Hamming space--a fundamental task with ubiquitous applications in nowadays eCommerce.…
Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines
Cun Mu, Jun Zhao, Guang Yang +2
A growing interest has been witnessed recently from both academia and industry in building nearest neighbor search (NNS) solutions on top of full-text search engines. Compared with…
Towards a simplified ontology for better e-commerce search
Aliasgar Kutiyanawala, Prateek Verma, Zheng +1
Query Understanding is a semantic search method that can classify tokens in a customer's search query to entities such as Product, Brand, etc. This method can overcome the limitati…
End-to-End Neural Ranking for eCommerce Product Search: an application of task models and textual embeddings
Eliot Brenner, Jun Zhao, Aliasgar Kutiyanawala +1
We consider the problem of retrieving and ranking items in an eCommerce catalog, often called SKUs, in order of relevance to a user-issued query. The input data for the ranking are…
Towards Practical Visual Search Engine within Elasticsearch
Cun Mu, Jun Zhao, Guang Yang +2
In this paper, we describe our end-to-end content-based image retrieval system built upon Elasticsearch, a well-known and popular textual search engine. As far as we know, this is…
Revisiting Skip-Gram Negative Sampling Model with Rectification
Cun Mu, Guang Yang, Zheng Yan
We revisit skip-gram negative sampling (SGNS), one of the most popular neural-network based approaches to learning distributed word representation. We first point out the ambiguity…