
## Homepage

Exploring and Verbalizing Academic Ideas by Concept Co-occurrence

[https://github.com/xyjigsaw/Kiscovery](https://github.com/xyjigsaw/Kiscovery)

## Co-occurrence Citation Quintuple

It is the official **Co-occurrence Citation Quintuple** dataset of paper *Exploring and Verbalizing Academic Ideas by Concept Co-occurrence*.

We construct and release a dataset of co-occurrence citation quintuples, which is used to train text generation model for idea verbalization. The process of identifying and processing concepts is similar to constructing the concept co-occurrence graph. Heuristic rules are adopted to filter redundant and noisy sentences, further improving the quality of the quintuples used for idea generation. More details of co-occurrence citation quintuples can be found in Appendix B, C, and J.


In mid-2023, our DeepReport system underwent a major update, encompassing both data and model improvements. On the data front, we introduced a new version of the quintuple data (V202306), resulting in enhanced quality and a larger-scale dataset. The statistical summary of the new quintuple data (V202306) is presented as follows:

| Discipline            | Quintuple | Concept | Concept Pair | Total $p$ | Total $p_1$ \& $p_2$ |
| --------------------- | --------- | ------- | ------------ | --------- | -------------------- |
| Art                   | 7,510     | 2,671   | 5,845        | 2,770     | 7,060                |
| History               | 5,287     | 2,198   | 4,654        | 2,348     | 5,764                |
| Philosophy            | 45,752    | 4,773   | 25,935       | 16,896    | 29,942               |
| Sociology             | 16,017    | 4,054   | 12,796       | 7,066     | 16,416               |
| Political Science     | 67,975    | 6,105   | 42,411       | 26,198    | 53,933               |
| Business              | 205,297   | 9,608   | 99,329       | 62,332    | 112,736              |
| Geography             | 191,958   | 12,029  | 118,563      | 42,317    | 112,909              |
| Engineering           | 506,635   | 16,992  | 249,935      | 137,164   | 273,894              |
| Geology               | 365,183   | 13,795  | 190,002      | 98,991    | 222,358              |
| Medicine              | 168,697   | 13,014  | 114,104      | 42,535    | 138,973              |
| Economics             | 227,530   | 9,461   | 113,527      | 68,607    | 131,387              |
| Physics               | 267,532   | 10,831  | 133,079      | 84,824    | 176,741              |
| Biology               | 224,722   | 15,119  | 145,088      | 59,210    | 189,281              |
| Mathematics           | 312,670   | 17,751  | 190,734      | 95,951    | 218,697              |
| Psychology            | 476,342   | 9,512   | 194,038      | 115,725   | 212,180              |
| Computer Science      | 531,654   | 16,591  | 244,567      | 151,809   | 238,091              |
| Environmental Science | 583,466   | 11,002  | 226,671      | 94,474    | 201,330              |
| Materials Science     | 573,032   | 17,098  | 249,251      | 145,068   | 313,657              |
| Chemistry             | 565,307   | 13,858  | 231,062      | 108,637   | 286,593              |
| **Total**             | 5,342,566 | 206,462 | 2,591,591    | 1,362,922 | 2,941,942            |

Note that each file is a list in the form of [[c_1, c_2, p, p_1, p_2], ...], the element of which is a quintuple. c_1 and c_2 are concepts, p is the target texts, i.e., the verbalized ideas.

Download with git

```bash
sudo apt-get install git-lfs
# OR
brew install git-lfs

git lfs install
git clone https://huggingface.co/datasets/Reacubeth/Co-occurrenceCitationQuintuple
```

## Citation

If you use our work in your research or publication, please cite us as follows:

```
@inproceedings{xu2023exploring,
  title={Exploring and Verbalizing Academic Ideas by Concept Co-occurrence},
  author={Xu, Yi and Sheng, Shuqian and Xue, Bo and Fu, Luoyi and Wang, Xinbing and Zhou, Chenghu},
  booktitle={Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL)},
  year={2023}
}
```

Please let us know if you have any questions or feedback. Thank you for your interest in our work!

license:gpl-3.0 region:us
{"license": "gpl-3.0"}
TAGS
#license-gpl-3.0 #region-us 

Homepage
--------


Exploring and Verbalizing Academic Ideas by Concept Co-occurrence


URL


Co-occurrence Citation Quintuple
--------------------------------


It is the official Co-occurrence Citation Quintuple dataset of paper *Exploring and Verbalizing Academic Ideas by Concept Co-occurrence*.


We construct and release a dataset of co-occurrence citation quintuples, which is used to train text generation model for idea verbalization. The process of identifying and processing concepts is similar to constructing the concept co-occurrence graph. Heuristic rules are adopted to filter redundant and noisy sentences, further improving the quality of the quintuples used for idea generation. More details of co-occurrence citation quintuples can be found in Appendix B, C, and J.


In mid-2023, our DeepReport system underwent a major update, encompassing both data and model improvements. On the data front, we introduced a new version of the quintuple data (V202306), resulting in enhanced quality and a larger-scale dataset. The statistical summary of the new quintuple data (V202306) is presented as follows:



Note that each file is a list in the form of [[c\_1, c\_2, p, p\_1, p\_2], ...], the element of which is a quintuple. c\_1 and c\_2 are concepts, p is the target texts, i.e., the verbalized ideas.


Download with git


If you use our work in your research or publication, please cite us as follows:


Please let us know if you have any questions or feedback. Thank you for your interest in our work!



TAGS
#license-gpl-3.0 #region-us 

passage: TAGS
#license-gpl-3.0 #region-us 
