I am using MS Word referencing functionality and I want to reference the sources by numbers while using APA style?
For example:
... see [1].
References:
[1] Rong, X. (2014). word2vec parameter learning explained. arXiv preprint arXiv:1411.2738.
How to do that?
Note: ISO-690 style has numerical referencing like (1), but I want to use [1] in the text and APA style in the references table.
APA does not support numerical referencing; what you're asking for is a violation of the APA referencing format.
In any event, this is an end-user question, not a programming one. As such, it is off-topic for StackOverflow.
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I am using PstgreSQL v12, and there is a native function \df jsonb_to_tsvector... But it is not described at pg guide functions-json neither other page. It is a interesting function, can I use it, is reliable? Or it is a kind of "lost in namespace" bug?
Important: even if google found it, I see citation absence (or absence of "also see" section) as a PG Guide bug. It is a jsonb_* native function: all must be cited at pg guide functions-json.
NOTES
At this old page of 2018 we can found something as:
CREATE TABLE test (id int, payload jsonb);
INSERT INTO test VALUES
(1,'{"glossary":{"title":"example glossary","GlossDiv":{"title":"S","GlossList":{"GlossEntry":{"ID":"SGML","Abbrev":"ISO 8879:1986","SortAs":"SGML","Acronym":"SGML","GlossDef":{"para":"A meta-markup language, used to create markup languages such as DocBook.","GlossSeeAlso":["GML","XML"]},"GlossSee":"markup","GlossTerm":"Standard Generalized Markup Language"}}}}}'::jsonb)
,(2,'{"menu":{"id":"file","popup":{"menuitem":[{"value":"New","onclick":"CreateNewDoc()"},{"value":"Open","onclick":"OpenDoc()"},{"value":"Close","onclick":"CloseDoc()"}]},"value":"File"}}'::jsonb)
,(3,'{"x":[1,2,3]}'::jsonb)
;
-- it is running and results are fine!
SELECT id, jsonb_to_tsvector('english', payload, '["all"]') FROM test;
SELECT id, jsonb_to_tsvector('english', payload, '["numeric","key"]') FROM test;
... and that it is "2 years lost".
(edited after answered)
Voting the IDEAL GUIDE
At answer comments #a_horse_with_no_name explain my position, "... with your logic, array_to_tsvector would need to be listed with the array functions...",
and that his position is the opposit.
The Stackoverflow community is democratic, we can use an efficient voting mechanism. I am creating a Wiki answer to you vote below as an alternative answer... Let's do an experiment. Each answer is an postion alternative:
vote this answer below for "no See also section" and no citations. You agree that Guide is good as it is, and a hub page not need to cite other functions.
vote this other answer below for "See also section" or completeness of citations. You agree that the Guide is not good, and a hub page need to cite other functions.
Time to vote at postgresql.org/docs?
I never understood why "our" PostgreSQL guide at postgresql.org/docs does not offer "See also" sections.
Almost all Wikipedia articles have a "See also" section, and almost all popular programming languages:
PHP example, PostGIS example, etc. or "see also" box like Python guide.
In a good programming language it is not difficult to classify and define groups of native functions, on the basis of shared characteristics.
PostgreSQL have a big community, so it is easy also to check consensus about defining groups of similar native functions... And sometimes is more easy: all functions with the prefix array_ are in the set of "all native array functions", all functions with the prefix jsonb_ are in the set of "all native JSONb functions".
It is also a kind of "completeness princicle for Guides": a Guide's page that explain "all functions of group G" need to explain, or at least to cite, all functions of the G group. The page "JSON functions" is for all native JSON functions, the page "ARRAY functions" is for all native JSON functions.
PS: about "native function" definition in this context, extensions are excluded from it. For example jsonb functions and array functions of extensions, like hstore are not native.
Problem: is there, at postgresql.org/docs, a democratic mechanism to vote, like here?
The function is documented in the text search functions
reduce each value in the document, specified by filter to a tsvector, and then concatenate those in document order to produce a single tsvector.
This answer is a Wiki (your vote goes to nobody) and is not a real answer, it is a kind of voting experient... I is a "place to vote" an alternative position. The two alternatives are:
here
and the
a_horse_with_no_name answer.
Position here: the Guide needs a "see also" section or similar thing
"See also section" or function name citations, for completeness in a "all native functions of group" page. Example: the page Guide of all native ARRAY functions, the page of all all native JSON functions, etc.
Vote here if you agree that the Guide is not good, and a hub page need to cite other functions.
I am trying to make chat bot. I searched for some solutions and programs to help me.
Can someone tell me if Program-o uses natural language processing?
I have searched on google but i didn't find the answer.
Program-O is basically the engine that uses recursive pattern-matching on AIML to find a suitable response.
The answer given here explains in a bit more detail NLP in AIML
The pertinent paragraph being:
If by "natural language processing" you mean what is commonly called a "learning bot," the ALICE (AIML) bot does not meet the definition. The ALICE program (whose "brain" is the AIML scripting language) is a pattern-matching program. It searches a fairly large database - usually about 40,000 entries - for a phrase or term that matches one in the input, then selects a reply from the set designated by the closest match. It neither writes to its own files or generates spontaneous output. It doesn't "learn" by itself. Any changes or new information must be hard-coded into the AIML files by the botmaster.
I have googled (well, DuckDuckGo'ed, actually) till I'm blue in the face, but cannot find a list of language codes of the type en-GB or fr-CA anywhere.
There are excellent resources about the components, in particular the W3C I18n page, but I was hoping for a simple alphabetical listing, fairly canonical if possible (something like this one). Cannot find.
Can anyone point me in the right direction? Many thanks!
There are several language code systems and several region code systems, as well as their combinations. As you refer to a W3C page, I presume that you are referring to the system defined in BCP 47. That system is orthogonal in the sense that codes like en-GB and fr-CA simply combine a language code and a region code. This means a very large number of possible combinations, most of which make little sense, like ab-AX, which means Abkhaz as spoken in Åland (I don’t think anyone, still less any community, speaks Abkhaz there, though it is theoretically possible of course).
So any list of language-region combinations would be just a pragmatic list of combinations that are important in some sense, or supported by some software in some special sense.
The specifications that you have found define the general principles and also the authoritative sources on different “subtags” (like primary language code and region code). For the most important parts, the official registration authority maintains the three- and two-letter ISO 639 codes for languages, and the ISO site contains the two-letter ISO 3166 codes for regions. The lists are quite readable, and I see no reason to consider using other than these primary resources, especially regarding possible changes.
There are 2 components in play here :
The language tag which is generally defined by ISO 639-1 alpha-2
The region tag which is generally defined by ISO 3166-1 alpha-2
You can mix and match languages and regions in whichever combination makes sense to you so there is no list of all possibilities.
BTW, you're effectively using a BCP47 tag, which defines the standards for each locale segment.
Unicode maintains such a list :
http://unicode.org/repos/cldr-tmp/trunk/diff/supplemental/index.html
Even better, you can have it in an XML format (ideal to parse the list) and with also the usual writing systems used by each language :
http://unicode.org/repos/cldr/trunk/common/supplemental/supplementalData.xml
(look in /LanguageData)
One solution would be to parse this list, it would give you all of the keys needed to create the list you are looking for.
http://www.iana.org/assignments/language-subtag-registry/language-subtag-registry
I think you can take it from here http://www.unicode.org/cldr/charts/latest/supplemental/territory_language_information.html
This can be found at Unicode's Common Locale Data Repository. Specifically, a JSON file of this information is available in their cldr-json repo
We have a working list that we work off of for language code/language name referencing for Localizejs. Hope that helps
List of Language Codes in YAML or JSON?
List of primary language subtags, with common region subtags for each language (based on population of language speakers in each region):
https://www.unicode.org/cldr/charts/latest/supplemental/language_territory_information.html
For example, for English:
en-US (320,000,000)
en-IN (250,000,000)
en-NG (110,000,000)
en-PK (100,000,000)
en-PH (68,000,000)
en-GB (64,000,000)
(Jukka K. Korpela and tigrish give good explanations for why any combination of language + region code is valid, but it might be helpful to have a list of codes most likely to be in actual use. s-f's link has such useful information sorted by region, so it might also be helpful to have this information sorted by language.)
Let's say I have a title string, written in different languages.
Is there way to check which language is each string?
I have not played with it but you should look at NSLinguisticTagger and its - (NSOrthography *)orthographyAtIndex:(NSUInteger)charIndex effectiveRange:(NSRangePointer)effectiveRange method. From the NSOrthography docs:
The NSOrthography class describes the linguistic content of a piece of
text, typically used for the purposes of spelling and grammar
checking.
An NSOrthography instance describes:
Which scripts the text contains. A dominant language and possibly
other languages for each of these scripts. A dominant script and
language for the text as a whole. Scripts are uniformly described by
standard four-letter tags (Latn, Grek, Cyrl, etc.) with the supertags
Jpan and Kore typically used for Japanese and Korean text, Hans and
Hant for Chinese text; the tag Zyyy is used if a specific script
cannot be identified. See Internationalization Programming Topics for
more information on internationalization.
Languages are uniformly described by BCP-47 tags , preferably in
canonical form; the tag und is used if a specific language cannot be
determined.
You can simply use the Google Transalate REST API to find the language.
And you can use something like RestKit to make the REST requests to the google servers.
You could use N-gram sampling frequencies techniques. I am not an expert, but they are rumored to work well in practice.
See netspeak and papers like this etc etc.
There's Google translation API available that allows language conversation. I am sure there must be something you will find that returns matched language for your string. See Google Translate APIs for details.
I'm curious if anyone understands, knows or can point me to comprehensive literature or source code on how Google created their popular passage blocks feature. However, if you know of any other application that can do the same please post your answer too.
If you do not know what I am writing about here is a link to an example of Popular Passages. When you look at the overview of the book Modelling the legal decision process for information technology applications ... By Georgios N. Yannopoulos you can see something like:
Popular passages
... direction, indeterminate. We have
not settled, because we have not
anticipated, the question which will
be raised by the unenvisaged case when
it occurs; whether some degree of
peace in the park is to be sacrificed
to, or defended against, those
children whose pleasure or interest it
is to use these things. When the
unenvisaged case does arise, we
confront the issues at stake and can
then settle the question by choosing
between the competing interests in the
way which best satisfies us. In
doing... Page 86
Appears in 15 books from 1968-2003
This would be a world fit for
"mechanical" jurisprudence. Plainly
this world is not our world; human
legislators can have no such knowledge
of all the possible combinations of
circumstances which the future may
bring. This inability to anticipate
brings with it a relative
indeterminacy of aim. When we are bold
enough to frame some general rule of
conduct (eg, a rule that no vehicle
may be taken into the park), the
language used in this context fixes
necessary conditions which anything
must satisfy... Page 86
Appears in 8 books from 1968-2000
more
It must be an intensive pattern matching process. I can only think of n-gram models, text corpus, automatic plagisrism detection. But, sometimes n-grams are probabilistic models for predicting the next item in a sequence and text corpus (to my knowledge) are manually created. And, in this particular case, popular passages, there can be a great deal of words.
I am really lost. If I wanted to create such a feature, how or where should I start? Also, include in your response what programming languages are best suited for this stuff: F# or any other functional lang, PERL, Python, Java... (I am becoming a F# fan myself)
PS: can someone include the tag automatic-plagiarism-detection, because i can't
Read this ACM paper by Kolak and Schilit, the Google researchers who developed Popular Passages. There are also a few relevant slides from this MapReduce course taught by Baldridge and Lease at The University of Texas at Austin.
In the small sample I looked over, it looks like all the passages picked were inline or block quotes. Just a guess, but perhaps Google Books looks for quote marks/differences in formatting and a citation, then uses a parsed version of the bibliography to associate the quote with the source. Hooray for style manuals.
This approach is obviously of no help to detect plagiarism, and is of little help if the corpus isn't in a format that preserves text formatting.
If you know which books are citing or referencing other books you don't need to look at all possible books only the books that are citing each other. If is is scientific reference often line and page numbers are included with the quote or can be found in the bibliography at the end of the book, so maybe google parses only this informations?
Google scholar certainly has the information about citing from paper to paper maybe from book to book too.