We have a posting analyzing requirement, that is, for a specific post, we need to return a list of posts which are mostly related to it, the logic is comparing the count of common tags in the posts. For example:
postA = {"author":"abc",
"title":"blah blah",
"tags":["japan","japanese style","england"],
}
there are may be other posts with tags like:
postB:["japan", "england"]
postC:["japan"]
postD:["joke"]
so basically, postB gets 2 counts, postC gets 1 counts when comparing to the tags in the postA. postD gets 0 and will not be included in the result.
My understanding for now is to use map/reduce to produce the result, I understand the basic usage of map/reduce, but I can't figure out a solution for this specific purpose.
Any help? Or is there a better way like custom sorting function to work it out? I'm currently using the pymongodb as I'm python developer.
You should create an index on tags:
db.posts.ensure_index([('tags', 1)])
and search for posts that share at least one tag with postA:
posts = list(db.posts.find({_id: {$ne: postA['_id']}, 'tags': {'$in': postA['tags']}}))
and finally, sort by intersection in Python:
key = lambda post: len(tag for tag in post['tags'] if tag in postA['tags'])
posts.sort(key=key, reverse=True)
Note that if postA shares at least one tag with a large number of other posts this won't perform well, because you'll send so much data from Mongo to your application; unfortunately there's no way to sort and limit by the size of the intersection using Mongo itself.
Related
EDIT At the suggestion of #HighPerformanceMark, I've moved the question to mathematica.stackexchange.com: my question, so I attempted to close the question here. But SO doesn't allow me to do it properly, hence this up-front warning.
Setup
Say, I'm given a dataset, like the one below:
titanic = ExampleData[{"Dataset", "Titanic"}]; titanic
Answering with:
And I want to count the occurrences of any combination between { "1st", "2nd"} and {"female", "male"}, using the Counts operator on the dataset, like:
genderclasscounts = titanic[All, {"class", "sex"}][Counts]
Problem statement
This is not a "flat" dataset and I don't have a clue how to query in the usual way, like:
genderclasscount[Select[ ... ], ...]
The resulting dataset doesn't provide "column" names to be used as parameters in the Select nor can I refer to the number representing the count by a name.
And I've no clue how to express an Association as a value in a Select!?
Furthermore, try genderclasscount[Print], this demonstrates the values presented to the operation over this dataset are just numbers!
An unsatisfactory attempt
Of course, I can "flatten" the Counts result, by doing something horrific and inefficient like:
temp = Dataset[(row \[Function]
AssociationThread[{"class", "sex", "count"} -> row]) /# (Nest[
Normal, genderclasscounts, 3] /.
Rule[{Rule["class", class_], Rule["sex", sex_]},
count_] -> {class, sex, count})]
In this form it is easy to query a count result:
First#temp[Select[#class == "1st" \[And] #sex == "female" &], "count"]
Question
So, my questions are
How can I query the (immediate) result of the Count operation in a convenient and efficient fashion, like using a Select operation on the resulting dataset? Or, if that is not possible;
Is there an efficient and convenient transformation of the Counts result dataset possible facilitating such a query? With "convenient" I mean, for example, that you just provide the dataset and the transformation handles the rest. So, not something like I've shown above in my unsatisfactory "solution" ;-)
Thanks for reading this far and I'm looking forward to anwsers and inspiration.
/#nanitous
Is there any way to ignore "stop words" while sorting.
For example:
I have words like
dixit
singla
the marklogic
On sorting in descending order the result should be
singla, the marklogic, dixit
As in the above example the is ignored.
Any way to achieve this?
Update:
Stop word can occur at any place.
for example
the MarkLogic
MarkLogic is the best
the MarkLogic is awesome
while sorting should not consider any stop word in the text.
Above is just a small example to describe the problem.
In actual I am using search:search API.
For sorting, I am using sort-order search options.
The element on which I have to perform sorting is dynamic. There are approx 30-35 elements.
Is there any way to customize the collation at this level like to configure some words (stop words) which will be ignored while sorting.
There is no standard collation URI that is going to do this for you (at least none that I've ever seen). You can do it dynamically, of course, by sorting on the result of a function invocation, but if you want it done efficiently at scale (and available to search:search), then you need to materialize the sortable string into your document. I've often done this as an attribute on the element:
<title sortable="Great Gatsby, The">The Great Gatsby</title>
Then you put a range index on the title/#sortable attribute.
You can also use the "envelope pattern" where materialized metadata like this is maintained in its own section of the document with the original kept in its own section. For things like this, I think it's a bit more elegant to decorate the elements directly, to keep the context.
If I understand your question correctly you're trying to get rid of the definite article when sorting your result-set.
In order to do this you need to use some additional functions and create a 'sort' criteria. My solution would look like this (I'm also including some sample documents so that you can test this just by copy-pasting):
(:
xdmp:document-insert("/peter.xml", <person><firstName>Peter</firstName><lastName>O'Toole</lastName><age>60</age></person>);
xdmp:document-insert("/john.xml", <person><firstName>John</firstName><lastName>Adams</lastName><age>18</age></person>);
xdmp:document-insert("/simon.xml", <person><firstName>Simon</firstName><lastName>Petrov</lastName><age>22</age></person>);
xdmp:document-insert("/mark.xml", <person><firstName>Mark</firstName><lastName>the Lord</lastName><age>25</age></person>);
:)
for $person in /person
let $sort := fn:reverse(fn:tokenize($person/lastName, ' '))[1]
order by $sort
(: return $person :)
return $person/lastName/text()
Notice that now the sort order is going to be
- Adams
- the Lord
- O'Toole
- Petrov
I hope this will help.
I've recently swapped from using Lucene for Sitecore to Solr.
For the most part it has been smooth, but the way I was writing some queries (using Sitecore.ContentSearch.Linq) abstraction now don't seem to be compatible.
Specifically, I have a situation where I've got "global" content and "regional" content, like so:
Home (000)
X
Y
Z
Regions (ID: 111)
Region 1 (ID: 221)
A
B
Region 2 (ID: 222)
D
My code worked on Lucene, but now doesn't on Solr. It should find all "global" and a single region's content, excluding all other region's content. So as an example, if the user's current region was Region 1, I'd want the query to return content X, Y, Z, A, B.
Sitecore's Item Crawler has a field for each item in the index called "_path" which is a multivalued string field of IDs, so as an example, Region 1's _path field value would be [000, 111, 221 ].
When I write this using the Linq abstraction it comes out as below which doesn't return results.
-_path:(111) OR _path:(221)
But _path:(111) does return result. Mind blown.
When I use the Solr interface and wrap each side of the OR in extra brackets like below (which I'd consider redundant) it works! Mind blown v2.
(-_path:(111)) OR (_path:(221))
Firstly, what's the difference between those queries?
Secondly, my real problem is I can't add these extra brackets as I'm working in an abstraction Linq so the brackets will be "optimized" out.
Any advice would be awesome! Cheers.
The problem here is, lucene's negative queries don't work like you think they do. They only remove results from what has been found. -_path:111 doesn't find all documents which aren't in 111, it doesn't find anything at all. It only removes results. So you are finding all results with path "221", then removing any that also have path "111", which from your heirarchy, I assume is all of them. See my answer here for a bit more on that topic.
The OR makes it seem like it ought to work, but really -_path:(111) OR _path:(221) is the same as -_path:(111) _path:(221). The moral here is: Don't use Lucene's AND/OR/NOT syntax, if you can help it. Use +/-. +/- syntax actually expresses how the query operates, AND/OR/NOT doesn't. It attempts to shoehorn it into a different, SQL-like retrieval model and leads to some unexpected behavior like this.
So, what about: (-_path:(111)) OR (_path:(221))
Well, first, does it actually work? Or does it just get some results?
If it just gets some results, but just seems to get the same results as _path:221: The reason is -_path:111 gets no results, so your query is, in practice, something like: (nothing) OR (_path:221), which is equivalent to _path:221
If it really does get the results you expect (I'm guessing it probably does): Something is translating your query into something like: (*:* -_path:111) (_path:221). Solr does have some logic along these lines, though I'm not quite sure in this case. Essentially, it puts a match-all in front of any lonely negative queries it finds, allowing them to do what you were expecting. If the implicit *:* makes you nervous about performance, well, it should. But lucene is an inverted index, it does well with finding matches on a term quickly. Getting everything that doesn't match goes against the grain of that retrieval model, and will pretty much have to do a full scan of the index.
I am working on an untrained classifier model. I am working in Python 2.7. I have a loop. It looks like this:
features = [0 for i in xrange(len(dictionary))]
for bgrm in new_scored:
for i in xrange(len(dictionary)):
if bgrm[0] == dictionary[i]:
features[i] = int(bgrm[1])
break
I have a "dictionary" of bigrams that I have collected from a data set containing customer reviews and I would like to construct feature arrays of each review corresponding to the dictionary I have created. It would contain the frequencies of the bigrams found within the review of the features in the dictionary (I hope that makes sense). new_scored is a list of tuples which contains the bigrams found within a particular review paired with their relative frequency of occurrence in that review. The final feature arrays will be the same length as the original dictionary with few non zero entries.
The above works fine but I am looking at a data set of 13000 reviews, for each review to loop through this code is going to take for eeever (if my computer doesnt run out of RAM first). I have been sitting with it for a while and cannot see how I can condense it.
I am very new to python so I was hoping a more experienced could help with condensing it or perhaps point me in the right direction towards a library that will contain the function I need.
Thank you in advance!
Consider making dictionary an actual dict object (or some fancier subclass of dict if it better suits your needs), as opposed to an iterable (list or tuple seems like what it is now). dictionary could map bigrams as keys to an integer identifier that would identify a feature position.
If you refactor dictionary that way, then the loop can be rewritten as:
features = [0 for key in dictionary]
for bgram in new_scored:
try:
features[dictionary[bgram[0]]] = int(bgrm[1])
except KeyError:
# do something if the bigram is not in the dictionary for some reason
This should convert what was an O(n) traversal through dictionary into a hash lookup.
Hope this helps.
I need to count how many times a particular node occurs in a document based on the values of two if its attributes. So, given the following small sample of XML:
<p:entry timestamp="2012-11-15T17:53:34.642-05:00" ticks="89709622449012" system="OSD" component="OSD5" marker=".\Launcher.cpp:1741" severity="Info" type="Driver" subtype="Start" tags="" sensitivity="false">
This can occur one or more times in the document with different attribute sets. I need to count how many show up with type="Driver" AND subtype="Start". I am able to count how many just have type="Driver" using:
count(//p:entry[#type="Driver"])
but haven't been able to combine them. This didn't work:
count(//p:entry[#type="Driver" and #subtype="Start"])
This works for the OP. Specify 2 predicates in succession instead of using operator and result in the same effect:
count(//p:entry[#type="Driver"][#subtype="Start"])
By right, the original code count(//p:entry[#type="Driver" and #subtype="Start"]) should work, as far as my knowledge goes.