An open-source online reverse dictionary.

Related tags

Deep Learning nlp natural-language-processing word reverse-dictionary
Overview

WantWords Logo

An open-source online reverse dictionary

What Is a Reverse Dictionary?

Opposite to a regular (forward) dictionary that provides definitions for query words, a reverse dictionary returns words semantically matching the query descriptions.

rd_example

What Can a Reverse Dictionary Do?

  • Solve the tip-of-the-tongue problem, the phenomenon of failing to retrieve a word from memory
  • Help new language learners
  • Help word selection (or word dictionary) anomia patients, people who can recognize and describe an object but fail to name it due to neurological disorder

Our System

Workflow

workflow

Core Model

The core model of WantWords is based on our proposed Multi-channel Reverse Dictionary Model [paper] [code], as illustrate in the following figure.

model

Pre-trained Models and Data

Download and decompress data and pretrained models to BASE_PATH/website_RD/.

Decompress data.rar under BASE_PATH/website_RD/.

Key Requirements

  • Django==2.2.5
  • django-cors-headers==3.5.0
  • numpy==1.17.2
  • pytorch-transformers==1.2.0
  • requests==2.22.0
  • scikit-learn==0.22.1
  • scipy==1.4.1
  • thulac==0.2.0
  • torch==1.2.0
  • urllib3==1.25.6
  • uWSGI==2.0.18
  • uwsgitop==0.11

Cite

If the code or data help you, please cite the following two papers.

@inproceedings{qi2020wantwords,
  title={WantWords: An Open-source Online Reverse Dictionary System},
  author={Qi, Fanchao and Zhang, Lei and Yang, Yanhui and Liu, Zhiyuan and Sun, Maosong},
  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  pages={175--181},
  year={2020}
}

@inproceedings{zhang2020multi,
  title={Multi-channel reverse dictionary model},
  author={Zhang, Lei and Qi, Fanchao and Liu, Zhiyuan and Wang, Yasheng and Liu, Qun and Sun, Maosong},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  pages={312--319},
  year={2020}
}
Comments
  • __Originally posted by @Yynny in https://github.com/camsong/You-Dont-Need-jQuery/issues/254__

    __Originally posted by @Yynny in https://github.com/camsong/You-Dont-Need-jQuery/issues/254__

    Originally posted by @Yynny in https://github.com/camsong/You-Dont-Need-jQuery/issues/254

    Originally posted by @Yynny in https://github.com/NabilAFK/nabilafk.github.io/issues/3

    opened by Yynny 2
  • 开源版本似乎未提供敏感词处理代码

    开源版本似乎未提供敏感词处理代码

    当查询词内包含敏感词时，线上部署版本会返回{"details":"The input description contains sensitive words","error":8,"message":"content error"}，在开源版本中未见此逻辑。

    opened by lwd-temp 1
  • 展示结果建议：对相关性极低的词语单独列一个 Section

    展示结果建议：对相关性极低的词语单独列一个 Section

    以“老婆”为例，在“老公”这个词后面的结果相关性没有那么强。或许可以为非专业用户做一点展示上的优化，按“高相关性”“中相关性”“低相关性”等进行分区或者分三列展示，并说明不同的可信程度。

    婆娘
女人
妻子
媳妇儿
太太
娘儿们
妻
妻室
娘子
爱人
婆姨
老伴
老婆子
夫人
老小
内助
老公
小老婆
丈母娘
肏
小姨子
儿媳妇
岳母
骚货
二奶
一男半女
二婚
小姑子
外遇
屄
戴绿帽子
小叔子
公婆
媳妇
大老婆
嫂子
闺女
女朋友
三妻四妾
公爹
婊子
大姨子
绿帽子
老娘
前妻
独守空房
情夫
沾花惹草
舅妈
贤惠
打光棍
丈夫
拈花惹草
富婆
贱货
男方
奶子
贤妻良母
荡妇
娶
嫁人
偷情
女方
守寡
守活寡
红杏出墙
娇妻
女友
鬼混
糟糠之妻
上床
淫妇
偷人
色鬼
知冷知热
男友
后妈
鸡巴
姐夫
妞
前夫
吃醋
孙媳妇
百依百顺
少奶奶
臭钱
嫂嫂
养老送终
女婿
小姑
花心
情妇
复婚
弟媳
爸
老大不小
再婚
家务活
千依百顺
婶子
    enhancement 
    opened by rijieli 1
  • Missing data file from given link in README.md

    Missing data file from given link in README.md

    Hi syheliel, First of all, your project is amazing, but downloaded data from the given link in README.md is insufficient to run the project (e.g., missing 'wordTrans_Ch_En_Sort.json', 'wordTrans_En_Ch_Sort.json', 'word2synset_synset.txt', etc.). It would be great if you can provide the link with such missing files.

    Thank you so much.

    opened by kimhung-uit 1
  • 词库太老了

    词库太老了

    汉-英反查： 搜索“新冠病毒”，结果如下： 1.retrovirus 2.HIV 3.viral 4.cytomegalovirus 5.virus 6.herpes zoster 7.antiviral 8.acyclovir 9.H1N1 10.virology

    正确结果应该是：Coronavirus

    enhancement 
    opened by lhggame 2
  • 能识别的字太少了

    能识别的字太少了

    刚才我验证了0x4e00到0x9fff的每一个汉字能否被识别（能出现相关近义词就是能识别，返回{"error": 1}就不能识别）

    验证代码：（可能需要数小时）

    import requests as r

result = 0
result_2 = 0
for i in range(0x4e01, 0x9fff + 1):
    t = r.get(f"https://wantwords.thunlp.org/ChineseRD/?description={chr(i)}&mode=CC")
    if i % 256 == 0:
        print(f"There are {result_2} unrecognizable characters in 256 characters({hex(i-256)}~{hex(i)}).")
        result_2 = 0
    if t.text == '{"error": 1}':
        result += 1
        result_2 += 1
print(result)

    结果显示：在所有的20992个汉字中，竟然有9033个汉字不能被识别，能识别的仅有11959个！

    因此，我觉得软件支持的汉字太少（CJK基本集支持度才57%，扩展区更加不行），很多不算太生僻的字都不能识别。可以考虑扩展词库了（肯定可以，有些不支持的汉字百度都能搜到）。

    enhancement todo 
    opened by QWERTY770 1
Owner
THUNLP
Natural Language Processing Lab at Tsinghua University
THUNLP
GitHub https://wantwords.thunlp.org/
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