Natural Language Processing Company
As a trusted natural language processing company, DashBouquet leverages the power of cutting-edge technology by empowering businesses worldwide with smart solutions.
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Natural Language Processing Company

Natural language processing is a branch of artificial intelligence aimed at bridging the gap between human communication and computer language by creating the means for machines not only for understanding words, but also for retrieving ideas, meaning and context from human speech. NLP draws upon research from the artificial intelligence branch of computer science, mathematics, computational linguistics, and several other disciplines. Although NLP technology is still evolving, there are many successful applications currently not just up and running, but transforming businesses in a profound way. That said, natural language processing services are currently in high demand.

Drive your digital transformation with our natural language processing services

DashBouquet offers multiple natural language processing services. Our NLP developers create custom tools for analyzing human-generated textual data allowing you to draw meaningful insights on your way to reaching your business goals.

language processing techniques

NLP companies widely use multiple language processing techniques, such as:
Stemming and Lemmatization
Stemming refers to the process of chopping words to their stems, and lemmatization is reducing words to their lemmas. Lemmatization is more accurate, as it uses the meaning of a word to arrive at its root word, but it is also time-consuming and requires more computational powers. Stemming algorithms are faster but prone to making more errors in reducing words. Both techniques are used to prepare text for further processing.
Tokenization technique involves splitting raw text into smaller pieces, or tokens, in order to improve search efficiency and optimize the use of storage space. This technique helps in interpreting the context and is used as a preparatory step in NLP model development.
Bag of Words
Bag of words is a technique used for pre-processing textual data to extract features that can be further used for modeling purposes. The algorithm elaborates word occurrence irrespective of its position within the text and creates a representation of the text.
Named Entity Recognition (NER)
Algorithms take textual input and identify entities such as names and nouns present in that text. This technique is used in multiple ways, such as for extracting keywords from news allowing for easy categorization; boosting search engine efficiency so that it can tag relevant information and store it separately; processing thousands customer reviews to identify critical issues.
Natural language generation
Natural language generation technique puts concepts into words. This technique converts structured dataset into natural language and can be used for instant generation of custom human-readable content for a number of simple domains. Natural language generation tools instantly create narratives, appropriate responses, and automated reports from raw data.
Sentiment Analysis
Sentiment analysis, or opinion mining, is a tool for identifying emotions within a given text. It can be used to gauge brand sentiment by instantly processing thousands of reviews and analyzing customer feedback. The technique uses various models allowing for interpreting and classifying sentiment based on polarity, emotions, and intentions.
Sentence Segmentation
Sentence segmentation refers to the process of breaking the texts into separate sentence units. The task is not trivial since boundary identification can be complicated by non-standard punctuation or ambiguity of punctuation marks. Training on a set of documents with pre-marked sentence breaks allows for better accuracy.

We provide natural language processing development services to companies of all sizes

DashBouquet provides custom natural language processing consulting services to help you neatly integrate NLP into your business. We will help you optimize multiple business processes with reliable natural language processing tools.

Applications of NLP include:

Search autocorrection and autocompletion
NLP-enabled tools allow for instant correction of misspelling and suggesting common words for completing search queries based on user search typing.
Language translation
Sophisticated algorithms of NLP drive advancements in language translation, making these tools reach more and more natural results.
Chatbots with NLP capabilities can extract meaning from users input and deliver more appropriate responses providing better conversational experience.
Email filtering
Implementation of NLP algorithms for processing email data allows to filter thousands of emails for certain keywords, and more accurate spam detection.
Survey analysis
Manual processing of open-ended survey responses can be automated with NLP-enabled solutions.
Targeted advertising
NLP algorithms process unstructured textual and audio user data and suggest contextually relevant ads for more effective targeting.
Hiring and recruitment
Natural language processing techniques are used in recruitment for analyzing CVs, screening candidates, facilitating unbiased decisions and optimal matches.
Voice assistants
Voice assistants can understand voice commands, perform suitable tasks or services, and respond with synthesized voices.
Grammar checkers
Grammar checking tools use multiple natural language processing algorithms to verify text for grammatical correctness.
Social media monitoring
Certain natural language processing techniques enable real-time public opinion gauging and uncovering sentiment across social media.