def search(self, query, lang, nostem = False):
if nostem:
originResults = self.engine.nostemSearch(query, lang)
else:
originResults = self.engine.search(query, lang)
terms = originResults['terms']
wordsTerms = originResults['wordsTerms']
queryStems = {normalizeWord(x, lang):x for x in wordsTerms}
### Modify context
modResult = self.engine.nostemSearch(' OR '.join(terms), lang)
modDoc, modTerms = self._getDocsAndTerms(modResult)
modContext = getContextFromSR(modDoc, modTerms, self.index.contains_term, self.maxKeywords)
modAttrsID = modContext.attrs2ids(terms)
originDocumentsID = {x['url'] for x in originResults['documents']}
modDocumentsID = {x['url'] for x in modDoc}
documentsID = originDocumentsID & modDocumentsID
documentsID = modContext.objects2ids(documentsID)
pq = str(originResults['parsedQuery'])
notAndQuery = ' OR ' in pq or 'NOT(' in pq
if notAndQuery:
modSearchConcept = self.getSearchConceptByObjects(modContext, documentsID)
else:
modSearchConcept = self._getSearchConceptByAttr(modContext, modAttrsID)
lowerN, upperN = self.getLowerUpper(modContext, modSearchConcept)
self.totalConcepts = set(lowerN | upperN)
jsonContext = modContext.getJSON()
jsonContext['attributes'] = [self.index.stem2word(x) for x in jsonContext['attributes']]
res = {'origin':originResults,
'specialization':self.getSpecialization(lowerN, modContext, terms, modSearchConcept),
'generalization':self.getGeneralization(upperN, modContext, terms, modSearchConcept, queryStems, notAndQuery),
'siblings':self.getSiblings(upperN, lowerN, modContext, modSearchConcept, queryStems),
'meta' : {'objects' : modContext.height, 'attributes' : modContext.width, 'context':jsonContext},
'suggestions' : self.getSuggestions(wordsTerms, len(originResults['documents']))}
namedLower = self.getNamedIntents(lowerN, modContext)
namedUpper = self.getNamedIntents(upperN, modContext)
namedSearchConcept = self.getNamedIntents([modSearchConcept], modContext)[0]
namedSiblings = self.getNamedIntents(self.siblings, modContext)
namedTrash = self.getNamedIntents(self.totalConcepts - (upperN | lowerN | self.siblings | {modSearchConcept}), modContext)
res['lattice'] = { 'lower' : namedLower, 'upper' : namedUpper,
'siblings' : namedSiblings, 'conceptintent' : namedSearchConcept,
'trash' : namedTrash, 'conceptextent' : list(modSearchConcept.extent)}
res['meta'].update({'lower' : len(lowerN), 'upper' : len(upperN), 'neighbor' : len(self.totalConcepts)})
return res
def search(self, query, lang, nostem=False):
if nostem:
originResults = self.engine.nostemSearch(query, lang)
else:
originResults = self.engine.search(query, lang)
terms = originResults['terms']
wordsTerms = originResults['wordsTerms']
queryStems = {normalizeWord(x, lang): x for x in wordsTerms}
### Modify context
modResult = self.engine.nostemSearch(' OR '.join(terms), lang)
modDoc, modTerms = self._getDocsAndTerms(modResult)
modContext = getContextFromSR(modDoc, modTerms,
self.index.contains_term,
self.maxKeywords)
modAttrsID = modContext.attrs2ids(terms)
originDocumentsID = {x['url'] for x in originResults['documents']}
modDocumentsID = {x['url'] for x in modDoc}
documentsID = originDocumentsID & modDocumentsID
documentsID = modContext.objects2ids(documentsID)
pq = str(originResults['parsedQuery'])
notAndQuery = ' OR ' in pq or 'NOT(' in pq
if notAndQuery:
modSearchConcept = self.getSearchConceptByObjects(
modContext, documentsID)
else:
modSearchConcept = self._getSearchConceptByAttr(
modContext, modAttrsID)
lowerN, upperN = self.getLowerUpper(modContext, modSearchConcept)
self.totalConcepts = set(lowerN | upperN)
jsonContext = modContext.getJSON()
jsonContext['attributes'] = [
self.index.stem2word(x) for x in jsonContext['attributes']
]
res = {
'origin':
originResults,
'specialization':
self.getSpecialization(lowerN, modContext, terms,
modSearchConcept),
'generalization':
self.getGeneralization(upperN, modContext, terms, modSearchConcept,
queryStems, notAndQuery),
'siblings':
self.getSiblings(upperN, lowerN, modContext, modSearchConcept,
queryStems),
'meta': {
'objects': modContext.height,
'attributes': modContext.width,
'context': jsonContext
},
'suggestions':
self.getSuggestions(wordsTerms, len(originResults['documents']))
}
namedLower = self.getNamedIntents(lowerN, modContext)
namedUpper = self.getNamedIntents(upperN, modContext)
namedSearchConcept = self.getNamedIntents([modSearchConcept],
modContext)[0]
namedSiblings = self.getNamedIntents(self.siblings, modContext)
namedTrash = self.getNamedIntents(
self.totalConcepts -
(upperN | lowerN | self.siblings | {modSearchConcept}), modContext)
res['lattice'] = {
'lower': namedLower,
'upper': namedUpper,
'siblings': namedSiblings,
'conceptintent': namedSearchConcept,
'trash': namedTrash,
'conceptextent': list(modSearchConcept.extent)
}
res['meta'].update({
'lower': len(lowerN),
'upper': len(upperN),
'neighbor': len(self.totalConcepts)
})
return res
def findWordIndex(self, content, word, lang): for i, w in enumerate(content): if normalizeWord(w, lang) == word: return i
