[
https://issues.apache.org/jira/browse/SOLR-9418?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Trey Grainger updated SOLR-9418:
--------------------------------
Description:
h2. *Summary:*
The Statistical Phrase Identifier is a Solr contribution that takes in a string
of text and then leverages a language model (an Apache Lucene/Solr inverted
index) to predict how the inputted text should be divided into phrases. The
intended purpose of this tool is to parse short-text queries into phrases prior
to executing a keyword search (as opposed parsing out each keyword as a single
term).
It is being generously donated to the Solr project by CareerBuilder, with the
original source code and a quickly demo-able version located here:
[https://github.com/careerbuilder/statistical-phrase-identifier|https://github.com/careerbuilder/statistical-phrase-identifier,]
h2. *Purpose:*
Assume you're building a job search engine, and one of your users searches for
the following:
_machine learning research and development Portland, OR software engineer AND
hadoop, java_
Most search engines will natively parse this query into the following boolean
representation:
_(machine AND learning AND research AND development AND Portland) OR (software
AND engineer AND hadoop AND java)_
While this query may still yield relevant results, it is clear that the intent
of the user wasn't understood very well at all. By leveraging the Statistical
Phrase Identifier on this string prior to query parsing, you can instead expect
the following parsing:
_{machine learning} \{and} \{research and development} \{Portland, OR}
\{software engineer} \{AND} \{hadoop,} \{java}_
It is then possile to modify all the multi-word phrases prior to executing the
search:
_"machine learning" and "research and development" "Portland, OR" "software
engineer" AND hadoop, java_
Of course, you could do your own query parsing to specifically handle the
boolean syntax, but the following would eventually be interpreted correctly by
Apache Solr and most other search engines:
_"machine learning" AND "research and development" AND "Portland, OR" AND
"software engineer" AND hadoop AND java_
h2. *History:*
This project was originally implemented by the search team at CareerBuilder in
the summer of 2015 for use as part of their semantic search system. In the
summer of 2016, Akash Mehta, implemented a much simpler version as a proof of
concept based upon publicly available information about the CareerBuilder
implementation (the first attached patch). In July of 2018, CareerBuilder open
sourced their original version
([https://github.com/careerbuilder/statistical-phrase-identifier),|https://github.com/careerbuilder/statistical-phrase-identifier,]
and agreed to also donate the code to the Apache Software foundation as a Solr
contribution. An Solr patch with the CareerBuilder version was added to this
issue on September 5th, 2018, and community feedback and contributions are
encouraged.
This issue was originally titled the "Probabilistic Query Parser", but the name
has now been updated to "Statistical Phrase Identifier" to avoid ambiguity with
Solr's query parsers (per some of the feedback on this issue), as the
implementation is actually just a mechanism for identifying phrases
statistically from a string and is NOT a Solr query parser.
h2. *Example usage:*
h3. (See contrib readme or configuration files in the patch for full
configuration details)
h3. *{{Request:}}*
{code:java}
http://localhost:8983/solr/spi/parse?q=darth vader obi wan kenobi anakin
skywalker toad x men magneto professor xavier{code}
h3. *{{Response:}}*
{code:java}
{
"responseHeader":{
"status":0,
"QTime":25},
"top_parsed_query":"{darth vader} {obi wan kenobi} {anakin skywalker}
{toad} {x men} {magneto} {professor xavier}",
"top_parsed_phrases":[
"darth vader",
"obi wan kenobi",
"anakin skywalker",
"toad",
"x-men",
"magneto",
"professor xavier"],
"potential_parsings":[{
"parsed_phrases":["darth vader",
"obi wan kenobi",
"anakin skywalker",
"toad",
"x-men",
"magneto",
"professor xavier"],
"parsed_query":"{darth vader} {obi wan kenobi} {anakin skywalker} {toad}
{x-men} {magneto} {professor xavier}",
"score":0.0}]}{code}
was:
The Statistical Phrase Identifier is a Solr contribution that takes in a string
of text and then leverages a language model (an Apache Lucene/Solr inverted
index) to predict how the inputted text should be divided into phrases. The
intended purpose of this tool is to parse short-text queries into phrases prior
to executing a keyword search (as opposed parsing out each keyword as a single
term).
History
This project was originally implemented at CareerBuilder in the summer of 2015
for use as part of their semantic search system. In 2018
The main aim of this requestHandler is to get the best parsing for a given
query. This basically means recognizing different phrases within the query. We
need some kind of training data to generate these phrases. The way this project
works is:
1.)Generate all possible parsings for the given query
2.)For each possible parsing, a naive-bayes like score is calculated.
3.)The main scoring is done by going through all the documents in the training
set and finding the probability of bunch of words occurring together as a
phrase as compared to them occurring randomly in the same document. Then the
score is normalized. Some higher importance is given to the title field as
compared to content field which is configurable.
4.)Finally after scoring each of the possible parsing, the one with the
highest score is returned.
> Statistical Phrase Identifier
> -----------------------------
>
> Key: SOLR-9418
> URL: https://issues.apache.org/jira/browse/SOLR-9418
> Project: Solr
> Issue Type: New Feature
> Security Level: Public(Default Security Level. Issues are Public)
> Reporter: Akash Mehta
> Priority: Major
> Attachments: SOLR-9418.patch, SOLR-9418.zip
>
>
> h2. *Summary:*
> The Statistical Phrase Identifier is a Solr contribution that takes in a
> string of text and then leverages a language model (an Apache Lucene/Solr
> inverted index) to predict how the inputted text should be divided into
> phrases. The intended purpose of this tool is to parse short-text queries
> into phrases prior to executing a keyword search (as opposed parsing out each
> keyword as a single term).
> It is being generously donated to the Solr project by CareerBuilder, with the
> original source code and a quickly demo-able version located here:
> [https://github.com/careerbuilder/statistical-phrase-identifier|https://github.com/careerbuilder/statistical-phrase-identifier,]
> h2. *Purpose:*
> Assume you're building a job search engine, and one of your users searches
> for the following:
> _machine learning research and development Portland, OR software engineer AND
> hadoop, java_
> Most search engines will natively parse this query into the following boolean
> representation:
> _(machine AND learning AND research AND development AND Portland) OR
> (software AND engineer AND hadoop AND java)_
> While this query may still yield relevant results, it is clear that the
> intent of the user wasn't understood very well at all. By leveraging the
> Statistical Phrase Identifier on this string prior to query parsing, you can
> instead expect the following parsing:
> _{machine learning} \{and} \{research and development} \{Portland, OR}
> \{software engineer} \{AND} \{hadoop,} \{java}_
> It is then possile to modify all the multi-word phrases prior to executing
> the search:
> _"machine learning" and "research and development" "Portland, OR" "software
> engineer" AND hadoop, java_
> Of course, you could do your own query parsing to specifically handle the
> boolean syntax, but the following would eventually be interpreted correctly
> by Apache Solr and most other search engines:
> _"machine learning" AND "research and development" AND "Portland, OR" AND
> "software engineer" AND hadoop AND java_
>
> h2. *History:*
> This project was originally implemented by the search team at CareerBuilder
> in the summer of 2015 for use as part of their semantic search system. In the
> summer of 2016, Akash Mehta, implemented a much simpler version as a proof of
> concept based upon publicly available information about the CareerBuilder
> implementation (the first attached patch). In July of 2018, CareerBuilder
> open sourced their original version
> ([https://github.com/careerbuilder/statistical-phrase-identifier),|https://github.com/careerbuilder/statistical-phrase-identifier,]
> and agreed to also donate the code to the Apache Software foundation as a
> Solr contribution. An Solr patch with the CareerBuilder version was added to
> this issue on September 5th, 2018, and community feedback and contributions
> are encouraged.
> This issue was originally titled the "Probabilistic Query Parser", but the
> name has now been updated to "Statistical Phrase Identifier" to avoid
> ambiguity with Solr's query parsers (per some of the feedback on this issue),
> as the implementation is actually just a mechanism for identifying phrases
> statistically from a string and is NOT a Solr query parser.
>
> h2. *Example usage:*
> h3. (See contrib readme or configuration files in the patch for full
> configuration details)
> h3. *{{Request:}}*
> {code:java}
> http://localhost:8983/solr/spi/parse?q=darth vader obi wan kenobi anakin
> skywalker toad x men magneto professor xavier{code}
>
> h3. *{{Response:}}*
>
> {code:java}
> {
> "responseHeader":{
> "status":0,
> "QTime":25},
> "top_parsed_query":"{darth vader} {obi wan kenobi} {anakin skywalker}
> {toad} {x men} {magneto} {professor xavier}",
> "top_parsed_phrases":[
> "darth vader",
> "obi wan kenobi",
> "anakin skywalker",
> "toad",
> "x-men",
> "magneto",
> "professor xavier"],
> "potential_parsings":[{
> "parsed_phrases":["darth vader",
> "obi wan kenobi",
> "anakin skywalker",
> "toad",
> "x-men",
> "magneto",
> "professor xavier"],
> "parsed_query":"{darth vader} {obi wan kenobi} {anakin skywalker}
> {toad} {x-men} {magneto} {professor xavier}",
> "score":0.0}]}{code}
>
>
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