Semantic Similarity Result interpretation - semantics

I'm performing a semantic similarity using a tool here,
I'm getting the following results, but cannot properly interprete them:
apple#n#1,banana#n#1 0.04809463683080774
apple#n#1,banana#n#2 0.13293629283742603
apple#n#2,banana#n#1 0.0
apple#n#2,banana#n#2 0.0
here is the code:
URL url = new URL ( "file" , null , "dictionary/3.0/dict" );
IDictionary dict = new Dictionary ( url ) ;
dict.open () ;
// look up first sense of the word " dog "
IIndexWord idxWord = dict . getIndexWord ( "dog" , POS.NOUN ) ;
IWordID wordID = idxWord . getWordIDs () . get (0) ; // 1 st meaning
List <IWordID> wordIDs = idxWord.getWordIDs();
JWS ws= new JWS ("dictionary", "3.0");
TreeMap <String,Double> scores1 = ws.getJiangAndConrath().jcn("apple", "banana", "n");
for (String s:scores1.keySet())
System.out.println(s+"\t"+scores1.get(s));

From the NLTK Documentation:
The Jiang Conrath similarity returns a score denoting how similar two
word senses are, based on the Information Content (IC) of the Least
Common Subsumer (most specific ancestor node) and that of the two
input Synsets. The relationship is given by the equation 1 / (IC(s1) +
IC(s2) - 2 * IC(lcs)).
A result of 0 means that the two concepts are not related at all.
A result near 1 would mean a very close relationship.

can you put me code source written in JAVA responsible for the execution of LeacockAndChodorow algorithm because I do have some problems with Url variable?

Related

How to retrieve the list of dynamic nested keys of BigQuery nested records

My ELT tools imports my data in bigquery and generates/extends automatically the schema for dynamic nested keys (in the schema below, under properties)
It looks like this
How can I get the list of nested keys of a repeated record ? so for example I can group by properties when those items have said property non-null ?
I have tried
select column_name
from my_schema.INFORMATION_SCHEMA.COLUMNS
where
table_name = 'my_table
But it will only list first level keys
From the picture above, I want, as a first step, a SQL query that returns
message
user_id
seeker
liker_id
rateable_id
rateable_type
from_organization
likeable_type
company
existing_attempt
...
My real goal through, is to group/count my data based on a non-null value of a 2nd level nested properties properties.filters.[filter_type]
The schema may evolve when our application adds more filters, so this need to be dynamically generated, I can't just hard-code the list of nested keys.
Note: this is very similar to this question How to extract all the keys in a JSON object with BigQuery but in my case my data is already in a shcema and it's not a JSON object
EDIT:
Suppose I have a list of such records with nested properties, how do I write a SQL query that adds a field "enabled_filters" which aggregates, for each item, the list of properties for wihch said property is not null ?
Example input (properties.x are dynamic and not known by the programmer)
search_id
properties.filters.school
properties.filters.type
1
MIT
master
2
Princetown
null
3
null
master
Example output
search_id
enabled_filters
1
["school", "type"]
2
["school"]
3
["type"]
Have you looked at COLUMN_FIELD_PATHS? It should give you the paths for all columns.
select field_path from my_schema.INFORMATION_SCHEMA.COLUMN_FIELD_PATHS where table_name = '<table>'
[https://cloud.google.com/bigquery/docs/information-schema-column-field-paths]
The field properties is not nested by array only by structures. Then a UDF in JavaScript to parse thise field should work fast enough.
CREATE TEMP FUNCTION jsonObjectKeys(input STRING, shownull BOOL,fullname Bool)
RETURNS Array<String>
LANGUAGE js AS """
function test(input,old){
var out=[]
for(let x in input){
let te=input[x];
out=out.concat(te==null ? (shownull?[x+'==null']:[]) : typeof te=='object' ? test(te,old+x+'.') : [fullname ? old+x : x] );
}
return out;
Object.keys(JSON.parse(input));
}
return test(JSON.parse(input),"");
""";
with tbl as (select struct(1 as alpha,struct(2 as x, 3 as y,[1,2,3] as z ) as B) A from unnest(generate_array(1,10*1))
union all select struct(null,struct(null,1,[999])) )
select *,
TO_JSON_STRING (A ) as string_output,
jsonObjectKeys(TO_JSON_STRING (A),true,false) as output1,
jsonObjectKeys(TO_JSON_STRING (A),false,true) as output2,
concat('["', array_to_string(jsonObjectKeys(TO_JSON_STRING (A),false,true),'","' ) ,'"]') as output_sring,
jsonObjectKeys(TO_JSON_STRING (A.B),false,true) as outpu
from tbl

Add array of other records from the same table to each record

My project is a Latin language learning app. My DB has all the words I'm teaching, in the table 'words'. It has the lemma (the main form of the word), along with the definition and other information the user needs to learn.
I show one word at a time for them to guess/remember what it means. The correct word is shown along with some wrong words, like:
What does Romanus mean? Greek - /Roman/ - Phoenician - barbarian
What does domus mean? /house/ - horse - wall - senator
The wrong options are randomly drawn from the same table, and must be from the same part of speech (adjective, noun...) as the correct word; but I am only interested in their lemma. My return value looks like this (some properties omitted):
[
{ lemma: 'Romanus', definition: 'Roman', options: ['Greek', 'Phoenician', 'barbarian'] },
{ lemma: 'domus', definition: 'house', options: ['horse', 'wall', 'senator'] }
]
What I am looking for is a more efficient way of doing it than my current approach, which runs a new query for each word:
// All the necessary requires are here
class Word extends Model {
static async fetch() {
const words = await this.findAll({
limit: 10,
order: [Sequelize.literal('RANDOM()')],
attributes: ['lemma', 'definition'], // also a few other columns I need
});
const wordsWithOptions = await Promise.all(words.map(this.addOptions.bind(this)));
return wordsWithOptions;
}
static async addOptions(word) {
const options = await this.findAll({
order: [Sequelize.literal('RANDOM()')],
limit: 3,
attributes: ['lemma'],
where: {
partOfSpeech: word.dataValues.partOfSpeech,
lemma: { [Op.not]: word.dataValues.lemma },
},
});
return { ...word.dataValues, options: options.map((row) => row.dataValues.lemma) };
}
}
So, is there a way I can do this with raw SQL? How about Sequelize? One thing that still helps me is to give a name to what I'm trying to do, so that I can Google it.
EDIT: I have tried the following and at least got somewhere:
const words = await this.findAll({
limit: 10,
order: [Sequelize.literal('RANDOM()')],
attributes: {
include: [[sequelize.literal(`(
SELECT lemma FROM words AS options
WHERE "partOfSpeech" = "options"."partOfSpeech"
ORDER BY RANDOM() LIMIT 1
)`), 'options']],
},
});
Now, there are two problems with this. First, I only get one option, when I need three; but if the query has LIMIT 3, I get: SequelizeDatabaseError: more than one row returned by a subquery used as an expression.
The second error is that while the code above does return something, it always gives the same word as an option! I thought to remedy that with WHERE "partOfSpeech" = "options"."partOfSpeech", but then I get SequelizeDatabaseError: invalid reference to FROM-clause entry for table "words".
So, how do I tell PostgreSQL "for each row in the result, add a column with an array of three lemmas, WHERE existingRow.partOfSpeech = wordToGoInTheArray.partOfSpeech?"
Revised
Well that seems like a different question and perhaps should be posted that way, but...
The main technique remains the same. JOIN instead of sub-select. The difference being generating the list of lemmas for then piping then into the initial query. In a single this can get nasty.
As single statement (actually this turned out not to be too bad):
select w.lemma, w.defination, string_to_array(string_agg(o.defination,','), ',') as options
from words w
join lateral
(select defination
from words o
where o.part_of_speech = w.part_of_speech
and o.lemma != w.lemma
order by random()
limit 3
) o on 1=1
where w.lemma in( select lemma
from words
order by random()
limit 4 --<<< replace with parameter
)
group by w.lemma, w.defination;
The other approach build a small SQL function to randomly select a specified number of lemmas. This selection is the piped into the (renamed) function previous fiddle.
create or replace
function exam_lemma_definition_options(lemma_array_in text[])
returns table (lemma text
,definition text
,option text[]
)
language sql strict
as $$
select w.lemma, w.definition, string_to_array(string_agg(o.definition,','), ',') as options
from words w
join lateral
(select definition
from words o
where o.part_of_speech = w.part_of_speech
and o.lemma != w.lemma
order by random()
limit 3
) o on 1=1
where w.lemma = any(lemma_array_in)
group by w.lemma, w.definition;
$$;
create or replace
function exam_lemmas(num_of_lemmas integer)
returns text[]
language sql
strict
as $$
select string_to_array(string_agg(lemma,','),',')
from (select lemma
from words
order by random()
limit num_of_lemmas
) ll
$$;
Using this approach your calling code reduces to a needs a single SQL statement:
select *
from exam_lemma_definition_options(exam_lemmas(4))
order by lemma;
This permits you to specify the numbers of lemmas to select (in this case 4) limited only by the number of rows in Words table. See revised fiddle.
Original
Instead of using a sub-select to get the option words just JOIN.
select w.lemma, w.definition, string_to_array(string_agg(o.definition,','), ',') as options
from words w
join lateral
(select definition
from words o
where o.part_of_speech = w.part_of_speech
and o.lemma != w.lemma
order by random()
limit 3
) o on 1=1
where w.lemma = any(array['Romanus', 'domus'])
group by w.lemma, w.definition;
See fiddle. Obviously this will not necessary produce the same options as your questions provides due to random() selection. But it will get matching parts of speech. I will leave translation to your source language to you; or you can use the function option and reduce your SQL to a simple "select *".

Force FsCheck to generate NonEmptyString for discriminating union fields of type string

I'm trying to achieve the following behaviour with FsCheck: I'd like to create a generator that will generate a instance of MyUnion type, with every string field being non-null/empty.
type MyNestedUnion =
| X of string
| Y of int * string
type MyUnion =
| A of int * int * string * string
| B of MyNestedUnion
My 'real' type is much larger/deeper than the MyUnion, and FsCheck is able to generate a instance without any problem, but the string fields of the union cases are sometimes empty. (For example it might generate B (Y (123, "")))
Perhaps there's some obvious way of combining FsCheck's NonEmptyString and its support for generating arbitrary union types that I'm missing?
Any tips/pointers in the right direction greatly appreciated.
Thanks!
This goes against the grain of property based testing (in that you explicitly prevent valid test cases from being generated), but you could wire up the non-empty string generator to be used for all strings:
type Alt =
static member NonEmptyString () : Arbitrary<string> =
Arb.Default.NonEmptyString()
|> Arb.convert
(fun (nes : NonEmptyString) -> nes.Get)
NonEmptyString.NonEmptyString
Arb.register<Alt>()
let g = Arb.generate<MyUnion>
Gen.sample 1 10 g
Note that you'd need to re-register the default generator after the test since the mappings are global.
A more by-the-book solution would be to use the default derived generator and then filter values that contain invalid strings (i.e. use ==>), but you might find it not feasible for particularly deep nested types.

Pig: Cast error while grouping data

This is the code that I am trying to run. Steps:
Take an input (there is a .pig_schema file in the input folder)
Take only two fields (chararray) from it and remove duplicates
Group on one of those fields
The code is as follows:
x = LOAD '$input' USING PigStorage('\t'); --The input is tab separated
x = LIMIT x 25;
DESCRIBE x;
-- Output of DESCRIBE x:
-- x: {id: chararray,keywords: chararray,score: chararray,time: long}
distinctCounts = FOREACH x GENERATE keywords, id; -- generate two fields
distinctCounts = DISTINCT distinctCounts; -- remove duplicates
DESCRIBE distinctCounts;
-- Output of DESCRIBE distinctCounts;
-- distinctCounts: {keywords: chararray,id: chararray}
grouped = GROUP distinctCounts BY keywords; --group by keywords
DESCRIBE grouped; --THIS IS WHERE IT GIVES AN ERROR
DUMP grouped;
When I do the grouped, it gives the following error:
ERROR org.apache.pig.tools.pigstats.SimplePigStats -
ERROR: org.apache.pig.data.DataByteArray cannot be cast to java.lang.String
keywords is a chararray and Pig should be able to group on a chararray. Any ideas?
EDIT:
Input file:
0000010000014743 call for midwife 23 1425761139
0000010000062069 naruto 1 56 1425780386
0000010000079919 the following 98 1425788874
0000010000081650 planes 2 76 1425721945
0000010000118785 law and order 21 1425763899
0000010000136965 family guy 12 1425766338
0000010000136100 american dad 19 1425766702
.pig_schema file
{"fields":[{"name":"id","type":55},{"name":"keywords","type":55},{"name":"score","type":55},{"name":"time","type":15}]}
Pig is not able to identify the value of keywords as chararray.Its better to go for field naming during initial load, in this way we are explicitly stating the field types.
x = LOAD '$input' USING PigStorage('\t') AS (id:chararray,keywords:chararray,score: chararray,time: long);
UPDATE :
Tried the below snippet with updated .pig_schema to introduce score, used '\t' as separator and tried the below steps for the input shared.
x = LOAD 'a.csv' USING PigStorage('\t');
distinctCounts = FOREACH x GENERATE keywords, id;
distinctCounts = DISTINCT distinctCounts;
grouped = GROUP distinctCounts BY keywords;
DUMP grouped;
Would suggest to use unique alias names for better readability and maintainability.
Output :
(naruto 1,{(naruto 1,0000010000062069)})
(planes 2,{(planes 2,0000010000081650)})
(family guy,{(family guy,0000010000136965)})
(american dad,{(american dad,0000010000136100)})
(law and order,{(law and order,0000010000118785)})
(the following,{(the following,0000010000079919)})
(call for midwife,{(call for midwife,0000010000014743)})

SQL Query in StarcounterDB

I have an SQL query problem in my Starcounter database where I want to write a query that retrieves html pages (Content) containing a specific set of keywords based on the following models.
class Keyword {
int Id;
string Text;
}
Example data:
Id Text
1 google
2 advertising
3 twitter
class Content {
int Id;
string Text;
}
Example data:
Id Text
4 "google advertising is nice for marketers"
5 "twitter is not a good way to get exposure"
class HasWord : Relation {
Keyword Keyword;
Content Content;
}
Example data:
Keyword Content
1 4
2 4
3 5
How would I write a Query that retrieves all Content containing 2 specific words, in this case "google" and "advertising"? Is it possible without nested queries?
Input:
"google" & "advertising"
Desired output:
"google advertising is nice for marketers"
If you need to find an instance of Content , which Text contains both words, then you can use operator LIKE with regular expression, which is described here. For example:
SELECT Text
FROM Content
WHERE Text LIKE '%google%' AND Text LIKE '%advertising%'
If you need to find an instance of Content, which is in relationship with both keywords, then you can use self-join. For example
SELECT r1.Content.Text
FROM HasWord r1, HasWord r2
WHERE r1.Content = r2.Content AND
r1.Keyword.Text = 'google' AND r2.Keyword.Text = 'advertising'
Note that the result of the query will contain duplicates.