use of org.apache.commons.text.similarity.CosineDistance in project goci by EBISPOT.
the class DiseaseTraitService method similaritySearch.
@Cacheable(value = "diseaseTraitAnalysis", key = "#analysisId")
public AnalysisCacheDto similaritySearch(List<AnalysisDTO> diseaseTraitAnalysisDTOS, String analysisId, double threshold) {
LevenshteinDistance lv = new LevenshteinDistance();
CosineDistance cd = new CosineDistance();
List<DiseaseTrait> diseaseTraits = diseaseTraitRepository.findAll();
List<AnalysisDTO> analysisReport = new ArrayList<>();
diseaseTraitAnalysisDTOS.forEach(diseaseTraitAnalysisDTO -> diseaseTraits.forEach(diseaseTrait -> {
String trait = diseaseTrait.getTrait();
String userTerm = diseaseTraitAnalysisDTO.getUserTerm();
double cosineDistance = cd.apply(userTerm, trait);
double levenshteinDistance = ((double) lv.apply(userTerm, trait)) / Math.max(userTerm.length(), trait.length());
double cosineSimilarityPercent = Math.round((1 - cosineDistance) * 100);
double levenshteinSimilarityPercent = Math.round((1 - levenshteinDistance) * 100);
double chosen = Math.max(cosineSimilarityPercent, levenshteinSimilarityPercent);
if (chosen >= threshold) {
AnalysisDTO report = AnalysisDTO.builder().userTerm(userTerm).similarTerm(trait).degree(chosen).build();
analysisReport.add(report);
}
}));
return AnalysisCacheDto.builder().uniqueId(analysisId).analysisResult(analysisReport).build();
}
use of org.apache.commons.text.similarity.CosineDistance in project goci by EBISPOT.
the class PublicationController method matchPublication.
@RequestMapping(value = "/match", produces = MediaType.APPLICATION_JSON_VALUE, method = RequestMethod.POST)
@ResponseBody
public ResponseEntity<Map<String, Object>> matchPublication(Model model, @RequestBody String pubmedId) {
Map<String, Object> results = new HashMap<>();
CosineDistance cosScore = new CosineDistance();
LevenshteinDistance levenshteinDistance = new LevenshteinDistance();
JaroWinklerSimilarity jwDistance = new JaroWinklerSimilarity();
EuropePMCData europePMCResult = europepmcPubMedSearchService.createStudyByPubmed(pubmedId);
Map<String, String> searchProps = new HashMap<>();
List<Map<String, String>> data = new ArrayList<>();
if (!europePMCResult.getError()) {
try {
searchProps.put("pubMedID", europePMCResult.getPublication().getPubmedId());
searchProps.put("author", europePMCResult.getFirstAuthor().getFullname());
searchProps.put("title", europePMCResult.getPublication().getTitle());
searchProps.put("doi", europePMCResult.getDoi());
results.put("search", searchProps);
String searchTitle = europePMCResult.getPublication().getTitle();
String searchAuthor = europePMCResult.getFirstAuthor().getFullname();
CharSequence searchString = buildSearch(searchAuthor, searchTitle);
Map<String, Submission> submissionMap = submissionService.getSubmissionsBasic();
for (Map.Entry<String, Submission> e : submissionMap.entrySet()) {
Map<String, String> props = new HashMap<>();
Submission submission = e.getValue();
String matchTitle = submission.getTitle();
String matchAuthor = submission.getAuthor();
CharSequence matchString = buildSearch(matchAuthor, matchTitle);
props.put("submissionID", submission.getId());
props.put("pubMedID", submission.getPubMedID());
props.put("author", submission.getAuthor());
props.put("title", submission.getTitle());
props.put("doi", submission.getDoi());
if (matchString.equals("")) {
props.put("cosScore", new Integer(0).toString());
props.put("levDistance", new Integer(0).toString());
props.put("jwScore", new Integer(0).toString());
} else {
Double score = cosScore.apply(searchString, matchString) * 100;
Integer ldScore = levenshteinDistance.apply(searchString, matchString);
Double jwScore = jwDistance.apply(searchString, matchString) * 100;
props.put("cosScore", normalizeScore(score.intValue()).toString());
props.put("levDistance", normalizeScore(ldScore).toString());
props.put("jwScore", new Integer(jwScore.intValue()).toString());
}
data.add(props);
}
data.sort((o1, o2) -> Integer.decode(o2.get("cosScore")).compareTo(Integer.decode(o1.get("cosScore"))));
} catch (IOException e) {
e.printStackTrace();
}
} else {
results.put("error", "ID " + pubmedId + " not found");
}
results.put("data", data);
model.addAttribute("baseUrl", depositionUiURL);
HttpHeaders responseHeaders = new HttpHeaders();
responseHeaders.add("Content-Type", "application/json; charset=utf-8");
return new ResponseEntity<>(results, responseHeaders, HttpStatus.OK);
}
Aggregations