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Testing and Issues

You can test this app and submit issues during the testing period of the Data Clustering Contest contest.

Entries with serious issues will not be able to win the contest, but even minor issues might be important for overall results.




#issue9825 – FIXED. Thanks to the Telegram Team.

P.S. This was not my problem at all – just 1 corrupted news file without a meta tag from the entire dataset. Solved by running on a fixed dataset.
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Fair Leopard Feb 28, 2020 at 15:11
Final score for this submission (out of 100):

Languages: 12.39
News EN: 28.72
News RU: 41.63
Categories EN: 33.4
Categories RU: 35.54
Threads EN: 38.7
Threads RU: 29.82
Top news EN: 45.26
Top news RU: 37.51

These data reflect the relative accuracy, precision and speed of the algorithm as compared to the other submissions.
Fair Leopard Feb 6, 2020 at 16:03
In our preliminary tests, this submission received the following scores (out of 100):

Languages: 96
News EN: 75
News RU: 80
Categories EN: 57
Categories RU: 58
Threads EN: 64
Threads RU: 45
Top EN: 75
Top RU: 63

This is not the final result, please stay tuned for updates. We apologize for the delay.
Fair Mammoth Feb 7, 2020 at 16:03
В ходе предварительного тестирования алгоритма были выявлены следующие недостатки в ранжировании:

– В разделе 'Main' отсутствует часть важных сюжетов, но при этом присутствуют множество нерелевантных.

– Часть заголовков в сюжетах – мнения. Заголовки другой части сюжетов слишком размытые (информация не подаётся в краткой нейтральной форме).

– Нерелевантная сортировка внутри некоторых сюжетов – статьи по другим темам отображаются выше релевантных.
Bright Ant Dec 12, 2019 at 19:09
DAMN. Looks like one of the articles hasn't <meta property="article:published_time"> tag. Unexpected issue. I tested a lot and didn't see articles without this tag. I thought it's a default meta tag for all of the internal view templates.
Any way to fix it with 1 line of code? T_T
Not accurate languages detection
Not accurate categorization (entertainment example)
In Russian, many news are wrongly filtered out as non-news
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