Name
Abstract | ||
|---|---|---|
Open source softwares play an important role in information retrieval research. Most of the existing open source information retrieval systems are implemented in Java or C++ programming language. In this paper, we propose Parrot1, a Python-based interactive platform for information retrieval research. The proposed platform has mainly three advantages in comparison with the existing retrieval systems: (1) It is integrated with Jupyter Notebook, an interactive programming platform which has proved to be effective for data scientists to tackle big data and AI problems. As a result, users can interactively visualize and diagnose a retrieval model; (2) As an application written in Python, it can be easily used in combination with the popular deep learning frameworks such as Tersorflow and Pytorch; (3) It is designed especially for researchers. Less code is needed to create a new retrieval model or to modify an existing one. Our efforts have focused on three functionalists: good usability, interactive programming, and good interoperability with the popular deep learning frameworks. To confirm the performance of the proposed system, we conduct comparative experiments on a number of standard test collections. The experimental results show that the proposed system is both efficient and effective, providing a practical framework for researchers in information retrieval.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3331184.3331393 | Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval |
Keywords | Field | DocType |
deep learning, information retrieval, python | Information retrieval,Computer science,Interoperability,Usability,Artificial intelligence,Deep learning,Interactive programming,Java,Big data,Python (programming language) | Conference |
ISBN | Citations | PageRank |
978-1-4503-6172-9 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinhui Tu | 1 | 5 | 2.24 |
| Jimmy Huang | 2 | 0 | 0.34 |
| Jing Luo | 3 | 8 | 1.14 |
| Runjie Zhu | 4 | 0 | 1.01 |
| Tingting He | 5 | 348 | 61.04 |