Hey everyone,

I got access to some logs and I've been slogging through the data. In particular, I've partially analyzed a sample of 100K zero-result full_text searches against enwiki, over the course of about an hour (2015-07-23 07:51:29 to 2015-07-23 08:55:42). My results and opinions are below.

TL;DR Summary: If these patterns hold for another sample (and across languages), we should be able to get some decent mileage out of these simple approaches:
- find sources of weird patterns and either ignore them, or contact the source and redirect them to a more appropriate destination
- use language or character set detection to redirect queries to other wikis
- filter the term "quot" from queries
- filter 14###########: from the front of queries
- replace _ with space in queries

All of this is somewhat rough, and exact numbers aren't guaranteed. Also the categories may overlap. I also intend to look for these same patterns from another sample from a different day and make sure they are more general and not just temporary idiosyncrasies. I also plan to look through other language wikis (i.e., Spanish and French to start) to see if there are cross-linguistic patterns like these.

I think we have to some how come to terms with the fact that some queries don't deserve results, and maybe figure out the source of such "illegitimate" queries and filter them. (I'd really like to be able to track down the referrer, if there is one, for a lot of the weirder queries.)

Top query:
- 248 Dounload feer game
- all via web... and Google can't find it. That's just weird.

Some other categories of queries are below. The numbers are "<total queries> / <unique queries>". Since this is a 100K sample of zero-result queries, and zero-results are about 25% of all results, each 1,000 of total queries here represents about 0.25% of all search queries.

253 / 171 string of numbers

3610 / 2505 no Latin letters
- I see Korean, Thai, Japanese, Cyrillic, doi #s (see below), Arabic, Hebrew, Greek, Armenian, Georgian, Devanagari, Burmese, Chinese, and some emoji (e.g., 11 searches for 😜💗🎨❤️💋😞☀️💦).
- I also saw instances of mixed Latin / non-Latin queries 
- Includes gibberish, which is hard to grep for, but easy to spot by eye
- Lots of the non-gibberish ones are clearly in other languages, and I saw queries in other Latin-alphabet languages go by, too.

2630 / 2627 DOIs, all in quotes

3015 / 1017 have quot in them (which gets auto-corrected to "quote", obviously)
- 327 are one word: quot ... quot
- I don't know where these are coming from, but they are weird. If we strip "quot" we would get many of these. This must be coming from some source that is adding quotes, then escaping them as "&quot;" and then stripping & and ;. Weird.

7155 / 6337 #:Name
- almost all are 14###########:Text
- e.g., 1436755654740:Sherlock Holmes
- These all look like Wikipedia titles!
- Two each of 0:... and 6000:...

114 / 85 actual http(s):// URLs

488 / 244 URL-like things starting with www... and ending with .com, .ru, etc.

211 / 132 other searches starting with “www.”

1085 / 1083 article searches in this format: ('"<TITLE>"', '<AUTHOR(S)>')

2457 / 2060 TV episodes (based on the presence of "S#E#"—that's season #, episode #)

8419 / 7523 AND boolean searches
703 / 701 OR boolean searches
- Many of these look auto-generated, esp in the aggregate. 
- For example: there are 498 / 249 "House_of_Gurieli" AND ... queries

6310 / 5742 queries with _ in them
- only 934 / 790 if we skip the 14###########:Text and boolean AND queries

Other things I noticed:

- lots of queries for books, articles, movies, tv, mp3s, and porn (in multiple languages)

- lots of "building up" searches (and these are all marked full_text), for example:
achevments o
achevments of
achevments of
achevments of h
achevments of he
achevments of hell
achevments of helle
achevments of hellen
achevments of hellen k
achevments of hellen k
achevments of hellen kell
achevments of hellen kelle
achevments of hellen keller

- reasonable-looking ~ queries don't work:
intitle:George~ intitle:Washin~ gives 0 results
intitle:Washington intitle:George gives 279 results

Finally, I did see a bunch of typos, but I didn't try to quantify them because I was digging into all of these other interesting patterns.

Have a good weekend.

Trey Jones
Software Engineer, Discovery
Wikimedia Foundation