R-universe search: lucene

Showing 5 of total 5 results (show query)

eu-ecdc

epitweetr:Early Detection of Public Health Threats from 'Twitter' Data

It allows you to automatically monitor trends of tweets by time, place and topic aiming at detecting public health threats early through the detection of signals (e.g. an unusual increase in the number of tweets). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords. More information is available in the 'epitweetr' peer-review publication (doi:10.2807/1560-7917.ES.2022.27.39.2200177).

Maintained by Laura Espinosa. Last updated 1 years ago.

early-warning-systems epidemic-surveillance lucene machine-learning signal-detection spark twitter

10.0 match 56 stars 5.98 score 86 scripts

trinker

lexicon:Lexicons for Text Analysis

A collection of lexical hash tables, dictionaries, and word lists.

Maintained by Tyler Rinker. Last updated 3 years ago.

hash lexicon lookup names-frequent stopwords text-dictionaries text-mining

4.0 match 111 stars 8.80 score 224 scripts 25 dependents

kasperwelbers

corpustools:Managing, Querying and Analyzing Tokenized Text

Provides text analysis in R, focusing on the use of a tokenized text format. In this format, the positions of tokens are maintained, and each token can be annotated (e.g., part-of-speech tags, dependency relations). Prominent features include advanced Lucene-like querying for specific tokens or contexts (e.g., documents, sentences), similarity statistics for words and documents, exporting to DTM for compatibility with many text analysis packages, and the possibility to reconstruct original text from tokens to facilitate interpretation.

Maintained by Kasper Welbers. Last updated 6 months ago.

cpp

2.2 match 31 stars 7.50 score 174 scripts 1 dependents

patzaw

BED:Biological Entity Dictionary (BED)

An interface for the 'Neo4j' database providing mapping between different identifiers of biological entities. This Biological Entity Dictionary (BED) has been developed to address three main challenges. The first one is related to the completeness of identifier mappings. Indeed, direct mapping information provided by the different systems are not always complete and can be enriched by mappings provided by other resources. More interestingly, direct mappings not identified by any of these resources can be indirectly inferred by using mappings to a third reference. For example, many human Ensembl gene ID are not directly mapped to any Entrez gene ID but such mappings can be inferred using respective mappings to HGNC ID. The second challenge is related to the mapping of deprecated identifiers. Indeed, entity identifiers can change from one resource release to another. The identifier history is provided by some resources, such as Ensembl or the NCBI, but it is generally not used by mapping tools. The third challenge is related to the automation of the mapping process according to the relationships between the biological entities of interest. Indeed, mapping between gene and protein ID scopes should not be done the same way than between two scopes regarding gene ID. Also, converting identifiers from different organisms should be possible using gene orthologs information. The method has been published by Godard and van Eyll (2018) <doi:10.12688/f1000research.13925.3>.

Maintained by Patrice Godard. Last updated 3 months ago.

1.8 match 8 stars 6.85 score 25 scripts

pommedeterresautee

unine:Unine Light Stemmer

Implementation of "light" stemmers for French, German, Italian, Spanish, Portuguese, Finnish, Swedish. They are based on the same work as the "light" stemmers found in 'SolR' <https://lucene.apache.org/solr/> or 'ElasticSearch' <https://www.elastic.co/fr/products/elasticsearch>. A "light" stemmer consists in removing inflections only for noun and adjectives. Indexing verbs for these languages is not of primary importance compared to nouns and adjectives. The stemming procedure for French is described in (Savoy, 1999) <doi:10.1002/(SICI)1097-4571(1999)50:10%3C944::AID-ASI9%3E3.3.CO;2-H>.

Maintained by Michaël Benesty. Last updated 6 years ago.

finish french german information-retrieval ir italian nlp portuguese spanish stemmer swedish cpp

0.5 match 4 stars 3.30 score 1 scripts