Text Analysis

Text Analysis

Our mission is to deliver affordable, quality Text Analytics services to our clients.It’s a broadly believed fact that nearby 80% of enterprise-relevant information initiates from text-based, unstructured sources. Social media, Emails, free-text survey queries and other sources hold huge, often unused potential to dig greater into customers’ experiences.

Keeping path of this, and extracting valuable customer experience material from it, is a rising task for many businesses. In reply to that contest, we have formed platform that uses NLP/ Deep Learning alongside with proprietary events to deliver 100% cloud based text analytics services to your organization.

Out of the box precision between 70-80%, Webtunix can provide high quality text analytics solutions which can become a turn-key in your business. We have brilliant minds and experts who has experience iin software engineering and data analysis, with the exposure to Business Intelligence and Market Research industry.Machine Learning for text analysis is best because it is based on statistical and mathematical models and extract accurate insights. On the one hand machine leanring handles text in a naive way.

Webtunix is a Machine Learning company in India who uses both directed and undirected procedures to examine text at ruler, comprising tokenization, clustering, lemmatization, key phrase, entity extraction, classification and rules-based tagging.

While many groups fight to get their arms about just organized data.It parts the vast majority of their formless content mainly untapped. Webtunix authorizes information workers at foremost enterprises to attach the full value of all their data. By automatically classifying key ideas, removing objects and examining sentimentality with multi-language support. Our Organization discloses the untapped professional value typically hidden unstructured text and unifies it with the related structured data to present a complete view.

Entity Extraction:

Webtunix detects and indexes multiple entities, such as people, companies, and locations.

Features Include:

Entities can be based on delivered, additional dictionaries, on patterns and rules. Entity extraction distributes with the standard product.

  • Key phrases to categorize information
  • Facets to ease data discovery
  • Filters to refine user queries

Sentimental Analysis:

Better understand your competition to improve business processes and the overall customer experience. Stay on the pulse and be actively aware of stakeholder perceptions about your brand, products or services.

Features Include:

  • Original technology to compute sentiment at an entity level and/or overall document level.
  • Graphically analyze alterations in sentiment over time.
  • Assessment and improve sentiment models spending thorough descriptions of sentiment scoring results.