Machine Translation

Automated translation. It is the process by which computer software is used to translate a text from one natural language to another. Secure and customized MT solution can build on corporate terminology and industry glossaries, and may be integrated within the company’s infrastructure.

Sentiment analysis

Identifying trends of public opinion from surveys, trying to determine trending themes and avoiding no efficient way to monitor the qualitative data coming in.

Text Categorization, Classification & Theme Extraction

This technology assigns texts to categories. Texts may belong to more than one category, categories may contain other categories.

Text Summarization

The most relevant portions of a text are extracted as a summary.

Full-text search

Texts are retrieved from a database that best match a given query or document. The candidate documents are ordered with respect to their expected relevance. Indexing, categorization, summarization and retrieval are often subsumed under the term information search.

Information Extraction

Relevant information pieces of information are discovered and marked for extraction. The extracted pieces can be: the topic, named entities such as company, place or person names, simple relations such as prices, destinations, functions etc. or complex relations describing accidents or company mergers.

• Named Entity Recognition
• Relationship Extraction

Keyword extraction

Identifying key concepts in set of documents.

Relationship Extraction

Extracted pieces of information from several sources are combined in one database.

Question Answering

Natural language queries are used to access information in a database. The database may be a base of structured data or a repository of digital texts in which certain parts have been marked as potential answers.

Language Generation

A report in natural language is produced that describes the essential contents or changes of a database. The report can contain accumulated numbers, maxima, minima and the most drastic changes.

Semantic Annotation

Attaching names, attributes, comments, descriptions, etc. to a document or to a selected part in a text. It provides additional information (metadata) about an existing piece of data.

Semantic Search

Data searching technique in a which a search query aims to not only find keywords, but to determine the intent and contextual meaning of the words a person is using for search.

Text Anonymization

Removing or replacing identity information from a document

 

Parsing

Grammatical analysis of certain text

Basic text processing

Sentence/word segmentation, part-of-speech-tagging, stemming, spell-checking, language detection.

Ontology Generation

Creating domain knowledge base