Comment by RugnirViking | Hacker News Reader

Comment by RugnirViking | Hacker News Reader

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Interesting ones I have found:

108 MusicQ: The musicality of the request. The results of the sorcerer Anton Konygin.

276 NightQuery: The request is set mainly at night (and accompanying ones for morning, afternoon etc)

316 IsUa: Domain in the .ua zone (ukraine)

747 WordHostWikiSum: The relative popularity of the Word -Host pair, where Word is the word from the Title article on Wikipedia, and the Host is the host that is referred to in this article.

755 NastyContent: Content ugliness factor. (several of the other factors related to port and "adult" content are defined as multiples of this)

892 ShortVideo: A document is a short video (Tiktok, Reels, Shorts)

894 TelegramPost: Document - post in telegram (note I could not find similar for twitter etc, but they do have for tiktok)

1076 More90SecVisitsShare: The share of visits for which the time spent during the day on the host is more than 90 seconds (they track how long users are spending on pages)

1078 RankHackedNovaPhp: Rank of hacked sites

1309 DistanceToAnkara: The distance from the city from where the request was set to Ankara

1603 YellowImgCount: Average yellow images count on host

1614 NewsAgencyRating: Rating of news agency from agencies.json (Yandex.News resource)

Everything in there makes sense imho except the Yellow Image Count. Anyone knows why that would be a factor?

It's been a long time since I've read it, but I vaguely remember a write-up many years ago (before we used ML for NSFW detection) about how either yellow images would often produce false positives in popular detection algos, and/or about how the yellow-ness of an image could be used as a lower-tech proxy for basic NSFW detection (seemingly because of its proximity to some common skin tones).

I don't know if either of these are relevant here, but it's possible a weight on Yellow Images could be related to NSFW images.

Upon closer inspection, they have a lot of weights regarding "yellowness" [0], and several of them say "based on Toloka", which is an antifraud service that assigns colors to violation levels [1].

So my suspicion above is probably wrong, and "yellow" images probably refer to a Toloka score/color for whatever domain the images are hosted on.

[0] https://yandex-explorer.herokuapp.com/search?q=yellow&o=all

[1] https://join.toloka.ai/blog/project-limits/

Wrong Toloka. Yandex has its own Toloka which is a crowdsourcing platform for repetitive tasks that inherently require a human in the loop. In other words, this factor comes from real human assessors hired via Toloka.

No, but can you explain the distance to Ankara one?

well now you're making me doubt myself, that's a weird one too. My first guess was "they need to know how far one request is from another, and Ankara is a good as any city"

So say suppose you're in New Orleans and I am in San Jose, now we can compare our distance, because geographical distance usually equates to cultural differences and perceptions of quality.

They have a Turkish version, so I guess this props up Turkish results to requests from Turkey (granted, Ankara is not exactly in the middle of the country ;-)

Ankara is the nearest city to Kırşehir, considered by some to be the geographical centre of the world (as viewed on a typical flat map).

there was exactly one other similar one (Distance to Madagan) which is a random russian town. So I think it might be deciding which of their datacenters should serve the request?

It is a bit funny to see people trying to guess the meaning of something which is a common knowledge elsewhere. Puts a perspective on all the talk about “modern, global, connected, automatically translated world”.

For a decade and a half, Yandex has had a codename for each big revision of search ranking algorithms and release of new search features. Most were city names, and Magadan was one of them. So “distance” is probably a distance to some rating introduced in that release. Whether it is a positive or negative factor (cutting obvious over-optimized sites), I have no idea.

Ankara is the capital of Turkey. For RU, UA & BY locales they have separate ranking models for queries from their capitals, but not for TR. Maybe, guessing, they did not have enough data to build two TR models and this additional input feature was good enough

I’m pretty sure yellow is a slang for a category of images. It could be ad images.

Could be! Perhaps as in Yellow Pages?

https://en.wikipedia.org/wiki/Yellow_journalism

In other words, clickbait images from clickbait ad networks.

> NewsAgencyRating: Rating of news agency from agencies.json

Was the agencies.json published?

sadly I couldn't find it. A lot of the entries make reference to their corporate wiki and intranet though so its possible it hasn't been released.

I agree though, would be very interesting indeed to see who they promote and/or push down

> 108 MusicQ: The musicality of the request. The results of the sorcerer Anton Konygin.

Sounds fascinating. Anyone have any idea what this is about? Is [0] the Konygin in question?

[0] https://orcid.org/0000-0002-0037-2352

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