Keyword Extraction is an open examination of text. It is a successful method aimed at the identification and recognition of keywords within given frameworks. The purpose is to generate AI (Artificial Intelligence) algorithms so as to enhance element and information extraction of terms from text data, that manually would be impossible to scan.
The approach aims at spotting and drawing text, and then transfer it to understandable and computer editable format. The user/developer inputs segments, there is pre-processing, scouring and finally output, with a precision of nearly 100%. You build a data set of related words, then with ML (Machine Learning) methods you identify frequent words and re-occurrences. It uses aligned sub-sequences to classify algorithms, in such a way to detect the message and what lies beneath.
Keyword Extractor API consists of a granular technique to identify the type of relationship between words. The purpose is to get a deeper insight into the evolution of judgement so as to allow better characterization of terms, by means of ML to extract keywords and key phrases automatically. The method is applied to multiple data sets, which adds efficiency to the process, requiring less input data, and thus making it simpler to operate.
Zyla Labs´ Keyword Extraction API, completes this approach with Wordsfinder Extractor API, Relevant Words Extractor API, Keyword Extractor API and Key Chunk Extractor API, which together build up an interesting suite of platforms for the automatization of word identification, recognition, extraction and processing. Recently the contributions and evolution of computational linguistics, applied linguists and computer engineers have managed to isolate words from texts. The aims are varied depending on the software and the purpose: text and keyword indexing, building knowledge databases, constructing corpus analysis, etc.
All systems aim to analyze set segments of text data so as to extract lists of words, or words in chunks, define frequency, establish relationship between terms, to meet the ultimate goal: to gauge the market`s judgement regarding a certain product or service that will enable the client to optimize productivity and make the correct decisions to improve.
Automatic identification of words is an ample category of technologies used to gather information from text data without manual data entry. Insights in messages in social media sites, blogs, forums, and even audio transcribed into readable texts, as well as many other sources can be scoured for useful information. The API identifies, validates, tracks and establishes interfaces with other systems, and serves a purpose to the user.
The output can be tailored to the client`s needs: barcodes, word clouds, percentages, word frequency, and digital data in general, that can be stored or used for another process. The latest developments in data processing and automation allow countless purposes that guarantee immediateness and easy processing.
A suite of available APIs ensures the automatic access to the necessary information that will allow your organization to introduce improvements and make adjustments to optimize your production of goods and/or services. A task that otherwise would be hard and slow when done manually, has become an “easy-peasy” way to obtain judgement from consumers, both about your company and your competitors`.
Such gathered data will allow you to make the changes that will in turn increase your sales and multiply your revenue, without the necessity of the expert team -who will be distracted from their basic labor- nor deriving human resources to a task that can be easily performed by an ordinary user.