Improving IR-Based Bug Localization with Context-Aware Query Reformulation
CODEC is a document and entity ranking dataset that focuses on complex essay-style topics.
Systematic Review Query Visualisation and Understanding Interface
NLP2API: Query Reformulation for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics.
A Convenient Field Study Toolkit (for our WWW21 paper Towards a Better Understanding of Query Reformulation Behavior in Web Search)
Replication package of RACK : Automated Query Reformulation for Code Search using Crowdsourced Knowledge
Extensible and Configurable Toolkit for Query Refinement Gold Standard Generation Using Transformers
Our CIKM21 Paper "Incorporating Query Reformulating Behavior into Web Search Evaluation"
The result of the work in this repo was published in the SIGIR 2019 paper: Information Needs, Queries, and Query Performance Prediction
The replication package for EMSE 2019 submission
Improving IR-Based Bug Localization with Context-Aware Query Reformulation
The tool implementation of the thesis work of Masud Rahman
Improving IR-Based Bug Localization with Context-Aware Query Reformulation
Class project for "Data Integration on Web" class of Università di Salerno, Computer Science Master degree. The platform is built using the knowledge acquired during the course to provide a service with which it is easy to find the ideal job.
Tool version of NLP2API technique
Information Retrieval, Information Extraction and Data Mining projects
RACK: Code Search in the IDE using Crowdsourced Knowledge
Evaluation code for Automated Query Expansion using High Dimensional Clustering
Combining Query Rewriting (PerfectRef) and Knowledge Graph Embeddings with Complex Query Answering
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