The final part of this chapter is devoted to symbol synonyms, which are unlike the synonyms we have discussed up until now. Symbol synonyms are string aliases used to represent symbols that would otherwise be removed during tokenization.
While most punctuation is seldom important for full text search, character combinations like emoticons may be very signficant, even changing the meaning of the the text. Compare:
-
I am thrilled to be at work on Sunday.
-
I am thrilled to be at work on Sunday :(
The standard
tokenizer would simply strip out the emoticon in the second
sentence, conflating two sentences that have quite different intent.
We can use the
{ref}analysis-mapping-charfilter.html#analysis-mapping-charfilter[mapping
character filter]
to replace emoticons with symbol synonyms like emoticon_happy
and
emoticon_sad
before the text is passed to the tokenizer:
PUT /my_index
{
"settings": {
"analysis": {
"char_filter": {
"emoticons": {
"type": "mapping",
"mappings": [ (1)
":)=>emoticon_happy",
":(=>emoticon_sad"
]
}
},
"analyzer": {
"my_emoticons": {
"char_filter": "emoticons",
"tokenizer": "standard",
"filter": [ "lowercase" ]
]
}
}
}
}
}
GET /my_index/_analyze?analyzer=my_emoticons
I am :) not :( (2)
-
The
mappings
filter replaces the characters to the left of⇒
with those to the right. -
Emits tokens:
i
,am
,emoticon_happy
,not
,emoticon_sad
.
It is unlikely that anybody would ever search for emoticon_happy
, but
ensuring that important symbols like emoticons are included in the index can
be very helpful when doing sentiment analysis. Of course, we could equally
have used real words, like happy
and sad
.
Tip
|
The mapping character filter is useful for simple replacements of exact
character sequences. For more flexible pattern matching, you can use regular
expressions with the
{ref}analysis-pattern-replace-charfilter.html[pattern_replace character filter].
|