So I am aware of how I could go about this myself, but anybody aware of any existing libraries which could handle this? (whatever language)?
This API is English-only, and has job title normalization: http://api.dataatwork.org/v1/spec/
Related
I am trying to implement synonym searching in the Examine search engine that comes with Umbraco 8 out of the box.
Does anyone have any experience with implementing synonym searching in Examine/Umbraco 8. The options that I have been considering after looking around are -
A package that can be installed in Umbraco 8 that offers this extended functionality (if one exists).
Implementing a custom index (currently just using the out of the box 'ExternalIndex') that somehow implements synonym searching in the analysis (via custom analyzer implementation etc - If that is even possible).
Manually formatting multiple search terms by checking for synonyms in the string beforehand, running all searches and consolidating the results after (really a nasty, last resort option - you don't have to tell me how bad this is, I already know).
I have been trawling around the forums for a definitive answer on this and cannot really find one. Essentially I want to stick with the Examine engine for simplicity, however I am starting to think that the best way to achieve what I am after would be to move to a new engine completely (elastic search for example).
Many thanks in advance.
Use algolia? It's free and will do what you need easily? https://www.algolia.com/
The Examine is based on something called the Lucene search index. Lucene is known to not really do synonyms I'm afraid (read why here and potential solution).
Your thinking is probably correct. Examine is good at what it does, if you want to use more advanced searching then you will be better off using a more advanced search provider. There are loads of options, Algolia is Saas and comes with a free plan depending on your usage. It's easy to install and you target data from the front-end.
YOu could also look into Azure Cognitive Search or Solr. These are probably harder to implement but will also do the job
I was reading Applying UML and Patterns.
In the FURPS+ section, I read this one for +:
Operations - system management in its operational setting.
I just can't understand this sentence and I can't map it to a non-functional requirement.
I would be appreciated if anyone could help me with it.
and another question:
as far as I know, the + part of FURPS+ is different in other sources. so what's the point of it? I think it's not clear enough.
as I read more, the book gives an example:
operational concerns (for example, how do errors get handled, or how often
to do backups?)
but the second question still remains...
I am working on a number of Rails-based projects which require spreadsheet-like functionality, so I would like to know if anyone ever tried to implement the Natural Order Recalculation algorithm in Ruby. If not, could you point out where can I find any guidelines so I can implement if myself. Oh, if anyone is interested, we will also open-source this part of our system :D
Best regards!
The term "natural ordering" in spreadsheets is a special case of a more general idea called topological sorting, in which a set of objects with dependencies are sorted in a way such that each object is processed only after the objects on which it depends. On this topic, I managed to find a few Ruby pages that describe topological sorting; this one might be a good starting point. Although this isn't exactly what you need, the fact that there appears to be some kind of library support may make your job substantially easier.
Hope this helps!
How to get the same results as http://developer.yahoo.com/search/content/V1/termExtraction.html
This question has been asked quite a few times before.
best approach to analyze text in PHP?
What is a good keyword extraction web service?
What is a simple way to generate keywords from a text?
Trying to approach this problem with existing solutions I stumbled upon "Text Analysis" Solr performs on the document before indexing as described in http://wiki.apache.org/solr/AnalyzersTokenizersTokenFilters - which includes stemming as well.
So the final index will consist mostly of terms used to describe the document.
Is there a solution that provides analyzers, tokenizers, and token filters for direct use? If solr is the way out, what is the best way get this data from solr's index?
Solr is a way to create a custom search engine. It does not seem to be the right tool for the job. The Wikipedia article about term extraction lists in its "external links" section several web applications for term extraction. OpenNLP has a list of tools which may be useful. Its Chunker may be helpful.
Just ask for the parsed terms e.g.
http://localhost:8983/solr/terms?terms.fl=text&terms.sort=count&terms.limit=-1
See TermsComponent
for more info.
What would be an intelligent way to store text, so that it can be intelligently parsed and translated later on.
For example, The employee is outstanding as he can identify his own strengths and weaknesses and is comfortable with himself.
The above could be the generic text which is shown to the user prior to evaluation. If the user is a Male (say Shaun) or female (say Mary), the above text should be translated as follows.
Mary is outstanding as she can identify her own strengths and weaknesses and is comfortable with herself.
Shaun is outstanding as he can identify his own strengths and weaknesses and is comfortable with himself.
How do we store the evaluation criteria in the first place with appropriate place or token holders. (In the above case employee should be translated to employee name and based on his gender the words he or she, himself or herself needs to be translated)
Is there a mechanism to automatically translate the text with the above information.
The basic idea of doing something like this is called Mail Merge.
This page seems to discus how to implement something like this in Ruby.
[Edit]
A google search gave me this - http://freemarker.org/
I don't know much about this library, but it looks like what you need.
This is a very broad question in the field of Natural Language Processing. There are numerous ways to go around it, the questions you asked seem too broad.
If I understand correctly part of your question this could be done this way :
#variable{name} is outstanding as #gender{he/she} can identify #gender{his/hers} own strengths and weaknesses and is comfortable with #gender{himself/herself}.
Or:
#name is outstanding as #he can identify #his own strengths and weaknesses and is comfortable with #himself.
... if gender is the major problem.
I have had some experience working with a tool called Grammatica, when building a custom user input excel like formula parsing and evaluation engine. It may not be to the level of sophistication you're looking for but it's a start. This basically uses many of the same concepts that popular code compiler parsers employ. It's definitely worth checking out.
I agree with Kornel, this question is too broad. What you seem to be talking about is semantics for which RDF's and OWL can be a good starting point. Read about modeling semantics using markup and you can work your way up from there.