Rosoka NLP v. Spark NLP
What is Natural Language Processing
Natural language processing (NLP) is a type of artificial intelligence used to understand and interpret human language. NLP was developed using computer science and computational linguistics to help fill the gaps between human language and computer understanding.
NLP can effectively carry out various tasks related to language, including sentiment analysis, topic, and language detection. NLP is also used to categorize languages and documents, and is commonly used to extract key phrases.
NLP software like Rosoka or Spark can be used to categorize documents and detect whether documents are spam or contain sensitive information, then subsequently process these documents.
Rosoka and Spark can both be used to score text for sentiment, which is an analysis of the text’s positive or negative tone based on the use of language. NLP software uses a process known as tokenization, where a text is split into smaller units like words or phrases. They also normalize words and map different forms of the same word to one another. NLP software can also identify a word’s part of speech, such as if it is a noun or verb, or detect whole sentences in paragraphs of text.
What are the options when choosing an NLP?
There are many different NLP software products on the market, with the most frequently used being Rosoka NLP and Spark NLP. If you’re looking for NLP software solutions, this article will compare the two products in detail.
Spark has created an accurate open-source NLP library. The software provides an easy-to-use API, which integrates with ML Pipelines. John Snow Labs commercially supports it.
Spark NLP uses a selection of effective operating procedures, including rule-based algorithms and machine learning. It also uses standard NLP functions such as tokenization, stemming, and lemmatization.
Spark provides users with very efficient speech tagging and sentiment analysis, as well as a spell checker and entity recognition.
One of the benefits of using Spark NLP is that the software can provide pre-trained pipelines and models. The Spark NLP library has been written using Scala, and includes Python APIs for use with Spark. Another significant advantage of the software is that it is not dependent on an ML library or on any other NLP.
When compared to Spark NLP, Rosoka’s software stands out for its multilingual capability, as it is able to analyze text in over 200 languages for digital forensic entity extraction. Rosoka can also be used as an add-on for other ADF products, whereas most other NLP software options are not.
Rosoka has English Language GIST capabilities, which allow the software to provide a basic understanding of the content of a document. It is able to identify and extract in over 200 languages, and provides summaries and glossaries in English, so there is no need to load separate dictionaries. Rosoka is not a full translation service; however, it helps those who want to summarize text in foreign languages. For example, Rosoka is used by investigators who want to quickly and easily identify potential evidence that could be important to their case. A user can load a document in a language they do not know with Rosoka and the software will accurately work it out.
Rosoka is a unique software, as it is able to identify approximately forty different entity types. The company has been running for over twenty-five years and creates very functional, effective, and accurate software that can be used across multiple languages.
Rosoka can summarize text quickly and accurately by identifying entities within the document. These entities are then used to create keyword tags within the text. The keywords allow users to search and retrieve documents, text, and information based on their content. Users can also create topics and use the software to produce summaries of a document’s important issues, which is useful for navigation purposes and to enumerate related documents in a preselected topic.
Which NLP is best?
The answer to which NLP software is right for you will depend on your industry’s needs. Spark offers basic functions, whereas Rosoka is much more sophisticated and ‘intelligent.’
While Spark is able to carry out entity extraction, the Rosoka NLP software can be easily customized to work with your specific industry standards by extracting entities important to your industry. This allows you to make decisions quickly and take action, no matter the language you’ve encountered.
If you’re searching for geospatial solutions for your company, Rosoka’s NLP software may be right for you. The company has created a unique multilingual software that works across a variety of industries. The software can provide multilingual solutions, entity and relationship extraction, geotagging, and sentiment and salience.
Contact Rosoka today to see how the NLP software can help your business operations.