人工智能/数据科学比赛汇总 2019.5

Dear 丶 2022-02-01 08:55 238阅读 0赞

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[![CodingNet.png][]][CodingNet.png 1]

## Named Entity Recognition and Relation Extraction for Portuguese ##

[http://www.inf.pucrs.br/linatural/wordpress/iberlef-2019/][http_www.inf.pucrs.br_linatural_wordpress_iberlef-2019]

18th March - 24th September, 2019 // Host by [IberLEF 2019][] // Prize: NaN

**Note**: The main objective of these tasks is to propose to participants the challenge of applying their systems/solutions to the activities of Named Entity Recognition (NER) and/or Relation Extraction (RE) in Portuguese texts.  
Task 1: Named Entity Recognition  
Task 2: Relation Extraction for Named Entities  
Task 3: General Open Relation Extraction

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## MEX-A3T: Authorship and aggressiveness analysis in Twitter: case study in Mexican Spanish ##

[https://sites.google.com/view/mex-a3t/][https_sites.google.com_view_mex-a3t]

18th March - 24th September, 2019 // Host by [IberLEF 2019][] // Prize: NaN

**Note**: The goal of the second edition of MEX-A3T is to further improve the research in these two important NLP tasks as well as to continue pushing the computational treatment of the Mexican Spanish. The MEX-A3T@IberLEF2019 has the following two tracks:  
[AUTHOR PROFILING TRACK][]  
[AGGRESSIVENESS DETECTION TRACK][]

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## 2019 搜狐校园算法大赛 ##

[https://www.biendata.com/competition/sohu2019/][https_www.biendata.com_competition_sohu2019]

03/20 - 05/22 2019 // Host by [Biendata][] // Prize: ￥75,000

**Note**: 给定若干文章，目标是判断文章的核心实体以及对核心实体的情感态度。每篇文章识别最多三个核心实体，并分别判断文章对上述核心实体的情感倾向（积极、中立、消极三种）。

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## Don’t Overfit! II ##

[https://www.kaggle.com/c/dont-overfit-ii][https_www.kaggle.com_c_dont-overfit-ii]

Now - May 7th, 2019 // Host by [Kaggle][] // Prize: Kaggle Swag

**Note**: A Fistful of Samples

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## Explorer Challenge: A $1million prize pool to find Australia’s next big mineral deposit ##

[https://unearthed.solutions/u/competitions/explorer-challenge][https_unearthed.solutions_u_competitions_explorer-challenge]

28 Feb - 31 May, 2019 // Host by [Unearthed][] // Prize: $1,000,000

**Note**: Join a global challenge to test the limits of data science and geology and develop new ideas about mineral exploration. OZ Minerals, a modern mining company, is opening up >2TB of their own private data from their exploration project, Mount Woods. Can you use this data to predict the next mineral deposit in South Australia? The winning models will be tested in real life, the top predictions will be drilled in 2019.

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## Habitat Challenge 2019 ##

[https://aihabitat.org/challenge/][https_aihabitat.org_challenge]

Apr 3 - May 19, 2019 // Host by [EvalAI][] & [Habitat Team][] & [CVPR 2019][] // Prize: $10k

**Note**: The objective of Habitat Challenge is to benchmark the state-of-the-art in goal-directed visual navigation around the PointGoal task as defined by Anderson et al. The challenge is built on top of the Habitat stack.

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## 2019 iQIYI Celebrity Video Identification Challenge ##

[http://challenge.ai.iqiyi.com/detail?raceId=5c767dc41a6fa0ccf53922e6][http_challenge.ai.iqiyi.com_detail_raceId_5c767dc41a6fa0ccf53922e6]

February 28 - July 8, 2019 // Host by [爱奇艺|iQIYI][iQIYI] & [AVS Workgroup][] // Prize: 6,000 US dollars

**Note**: The goal of the iQIYI-VID-2019 Challenge is as follows: For each identity in the training set, find all the video clips of the same identity in the test set. And the retrieval result list should be ordered according to the similarity between each test clip and the query.

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## Visual Dialog Challenge 2019 ##

[https://visualqa.org/challenge.html][https_visualqa.org_challenge.html]

Jan 29, 2019 - May 11, 2019 // Host by [EvalAI][EvalAI 1] & [CVPR 2019][CVPR 2019 1] // Prize: $10k for Google Cloud Platform

**Note**: Given an image and a natural language question about the image, the task is to provide an accurate natural language answer.

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## CARLA Autonomous Driving Challenge ##

[http://carlachallenge.org/challenge/][http_carlachallenge.org_challenge]

13 March - May 12, 2019 // Host by [EvalAI][EvalAI 2] // Prize: $8,000.00

**Note**: The CARLA Autonomous Driving challenge encourages the development of state-of-the-art autonomous driving systems to tackle complex traffic scenarios.  
Track 1 - LIDAR, GPS and Cameras. All sensors track, for robotics teams that want to leverage the power of sensor fusion.  
Track 2 - Cameras and GPS. Only cameras track, for brave ML teams that want to explore driving with cameras.  
Track 3 - HD map, waypoints and all sensors. Map-based track, for teams that want to exploit available AD stacks based on HD maps and pre-computed waypoints  
Track 4 - Scene layout. A perception-less track, for teams that don’t want to deal with perception and prefer to focus on planning and control aspects.

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## TASS 2019: Sentiment Analysis Task at SEPLN ##

[https://competitions.codalab.org/competitions/21957][https_competitions.codalab.org_competitions_21957]

March 7 - September 24, 2019 // Host by [CodaLab][] & [SEPLN2019][] & [IberLEF 2019][] // Prize: NaN

**Note**: The first aim of this task is the furtherance of research on sentiment analysis in Spanish with a special interest on the language used in Twitter.

> [**阅读更多**][DataSciComp]

[CodingNet.png]: /images/20220201/fea1fb76b0c14fa2a0db11a286ba7e3b.png
[CodingNet.png 1]: https://coding.net/?utm_source=ApacheCN&utm_medium=banner&utm_campaign=march2019
[DataSciComp]: https://iphysresearch.github.io/DataSciComp/
[iphysresearch_DataSciComp]: https://github.com/iphysresearch/DataSciComp
[ApacheCN]: https://www.apachecn.org/
[Link 1]: https://weibo.com/u/6326715527
[Link 2]: https://www.zhihu.com/people/apachecn
[CSDN]: https://blog.csdn.net/wizardforcel/article/category/8437073
[Link 3]: https://www.jianshu.com/c/4ee721d0c474
[OSChina]: https://my.oschina.net/repine/
[Link 4]: https://www.cnblogs.com/wizardforcel/category/1352397.html
[http_www.inf.pucrs.br_linatural_wordpress_iberlef-2019]: http://www.inf.pucrs.br/linatural/wordpress/iberlef-2019/
[IberLEF 2019]: https://sites.google.com/view/iberlef-2019/home
[https_sites.google.com_view_mex-a3t]: https://sites.google.com/view/mex-a3t/
[AUTHOR PROFILING TRACK]: https://sites.google.com/view/mex-a3t/tracks/AP?authuser=0
[AGGRESSIVENESS DETECTION TRACK]: https://sites.google.com/view/mex-a3t/tracks/AI?authuser=0
[https_www.biendata.com_competition_sohu2019]: https://www.biendata.com/competition/sohu2019/
[Biendata]: https://www.biendata.com/
[https_www.kaggle.com_c_dont-overfit-ii]: https://www.kaggle.com/c/dont-overfit-ii
[Kaggle]: https://www.kaggle.com/
[https_unearthed.solutions_u_competitions_explorer-challenge]: https://unearthed.solutions/u/competitions/explorer-challenge
[Unearthed]: https://unearthed.solutions/
[https_aihabitat.org_challenge]: https://aihabitat.org/challenge/
[EvalAI]: https://evalai.cloudcv.org/web/challenges/challenge-page/254/
[Habitat Team]: https://aihabitat.org/
[CVPR 2019]: http://cvpr2019.thecvf.com/
[http_challenge.ai.iqiyi.com_detail_raceId_5c767dc41a6fa0ccf53922e6]: http://challenge.ai.iqiyi.com/detail?raceId=5c767dc41a6fa0ccf53922e6
[iQIYI]: http://challenge.ai.iqiyi.com/
[AVS Workgroup]: http://www.avs.org.cn/english/index.asp
[https_visualqa.org_challenge.html]: https://visualqa.org/challenge.html
[EvalAI 1]: https://evalai.cloudcv.org/web/challenges/challenge-page/163
[CVPR 2019 1]: https://visualqa.org/workshop.html
[http_carlachallenge.org_challenge]: http://carlachallenge.org/challenge/
[EvalAI 2]: https://evalai.cloudcv.org/web/challenges/challenge-page/246/phases
[https_competitions.codalab.org_competitions_21957]: https://competitions.codalab.org/competitions/21957
[CodaLab]: https://competitions.codalab.org/
[SEPLN2019]: http://hitz.eus/sepln2019/