Natural Language Processing (NLP): Transforming AI & Data Insights

What is Natural Language Processing | Introduction to NLP

Author

mirketa

July 20, 2017

NLP sits at the intersection of computer science, artificial intelligence, and computational linguistics. By utilizing Natural Language Processing algorithms, developers can organize and structure textual data to perform tasks such as automatic summarization, translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation. (En.wikipedia.org, 2017)

Natural Language Processing is characterized as a hard problem in computer science since human language is rarely precise or plainly spoken. To understand human language, one must not only understand the words but their meaning & context and how they interconnect to form meaning. The vagueness and ambiguous nature of human language make it difficult to learn for computers while being easy to learn for humans.

Components of Natural Language Processing

There are two components of NLP which are listed as follows:

1. Natural Language Understanding(NLU)

This includes understanding the different aspects of the language and mapping the input text in natural language to useful representations. This is the harder of the two components since this section has to deal with the ambiguity & complexity of the language. There are mainly three levels of ambiguity which are as follows:

1.Word-level or Lexical Ambiguity

Syntax Level or Parsing Ambiguity
Referential Ambiguity

2. Natural Language Generation(NLG)

As evident from the name, NLG is the process of producing or generating meaningful phrases and sentences in the form of natural language. It involves text planning, sentence planning, and text realization.

NLP Terminology

Syntax: It refers to the arrangement of words that form a sentence. It also involves the determination of the structural role of each word in the sentence.
Phonology: It is the study of organizing sounds systematically.
Morphology: It is a study of how words are constructed using primitive meaningful units.
Semantics: It deals with the meaning of words and how they can be joined/combined to form meaningful sentences.
Discourse: This determines how the immediately preceding sentence can affect the interpretation of the next sentence.
Pragmatics: This deals with how the interpretation of a sentence changes according to the situation.

What can developers use NLP algorithms for?

Summarizing blocks of text to extract the meaningful information from the given text, ignoring the remaining non-relevant text
Understanding the input and generating the output in Chatbots
Deriving the sentiment of a piece of text using Sentiment analysis
Break up large text into simpler tokens such as sentences or words.

Some Open Source NLP Libraries

Apache OpenNLP

It is a Java based machine learning toolkit provided by Apache, that supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, language detection, and coreference resolution. OpenNLP also includes maximum entropy and perceptron based machine learning. It provides built-in Java classes for each function as well as a command-line interface for testing the pre-built agents.

Natural Language Toolkit(NLTK)

It is a platform for building Python programs to read and process human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum.

Stanford CoreNLP

Stanford CoreNLP provides a set of human language technology tools. It can give the base forms of words, their parts of speech, mark up the structure of sentences in terms of phrases and syntactic dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract or open-class relations between entity mentions, get the quotes people said, etc.

MALLET

MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. Apart from classification, MALLET includes tools for sequence tagging for applications such as named-entity extraction from text. Algorithms include Hidden Markov Models, Maximum Entropy Markov Models, and Conditional Random Fields.

These are few of the many open source libraries and toolkits available for development on Natural Language Processing which can be utilized by developers in their applications.
In conclusion, Natural Language Processing is an important part of the artificial intelligence field and needs to be given importance if someone wants to master the trade of Machine Learning or Artificial Intelligence.

Process Builder: Salesforce Automation Tool for Unleashing Efficiency

In our rapidly evolving world, precision and productivity are essential. Salesforce, a leading customer relationship management (CRM) platform, offers a suite of automation tools designed to streamline workflows and enhance productivity. Among these tools, Process Builder stands out for its versatility and user-friendly interface. This blog delves into the capabilities of Process Builder, highlighting its features, benefits, and best practices for maximizing its potential.

What is Process Builder?

Process Builder is a powerful automation tool within Salesforce that allows users to automate business processes using a simple point-and-click interface. Introduced as an upgrade to the traditional Workflow Rules, Process Builder provides more advanced capabilities, enabling users to create complex if/then statements and automate a broader range of tasks.

Key Features of Process Builder

Visual Interface: Process Builder’s visual interface makes it accessible to users with varying technical expertise. The drag-and-drop functionality allows users to design processes intuitively, without needing to write code.
Multiple Criteria and Actions: Unlike Workflow Rules, which are limited to a single action per rule, Process Builder supports multiple criteria and actions within a single process. This means you can define complex workflows with various if/then scenarios, streamlining multi-step processes.
Record Updates and Creation: Process Builder can automate the creation and updating of records. For instance, it can automatically create a new task when a lead is converted or update the status of an opportunity when certain conditions are met.
Email Alerts: Users can configure Process Builder to send automated email alerts based on specific triggers. This ensures timely communication and helps keep all stakeholders informed.
Invoking Other Processes: Process Builder can invoke other processes or flows, providing a modular approach to automation. This feature is particularly useful for breaking down complex processes into manageable components.
Scheduled Actions: Process Builder allows users to schedule actions at a specific time. This can be useful for follow-up tasks, such as sending reminder emails or updating records after a certain period.

Benefits of Using Process Builder

Increased Efficiency: By automating repetitive tasks, Process Builder frees up valuable time for employees to focus on higher-value activities. This leads to increased productivity and overall business efficiency.
Error Reduction: Automation minimizes the risk of human error, ensuring that processes are executed consistently and accurately.
Improved Consistency: Process Builder ensures that business processes are carried out uniformly, adhering to predefined rules and criteria.
Scalability: As companies expand, their operations tend to become more intricate. Process Builder’s ability to handle multiple criteria and actions within a single process makes it a scalable solution for growing organizations.
Enhanced Visibility: With Process Builder, users can easily track and monitor automated processes. This visibility helps in identifying bottlenecks and optimizing workflows for better performance.

Practical Applications of Process Builder

1. Lead Management: Automate lead assignment and follow-up tasks to ensure timely engagement. For example, when a new lead is created, Process Builder can automatically assign it to the appropriate sales representative and create a follow-up task.
2. Opportunity Management: Streamline opportunity management by automating updates and notifications. When an opportunity reaches a specific stage, Process Builder can update related records, send notifications to team members, and create tasks for the next steps.
3. Case Management: Enhance customer service by automating case escalations and follow-ups. Process Builder can route cases to the appropriate support tier based on predefined criteria and create tasks for follow-up actions.
4. Approval Processes: Simplify approval workflows by automating the routing of records for approval. For instance, when a discount request is submitted, Process Builder can automatically route it to the manager for approval and notify the requester of the decision.

Conclusion

Salesforce automation tools in 2024 continue to revolutionize business processes by streamlining operations, reducing manual effort, and enhancing efficiency. Whether it’s the versatile Flow Builder, user-friendly Process Builder, powerful Apex, or intelligent Einstein Next Best Action, these tools offer a comprehensive solution for automating complex workflows, improving accuracy, and driving business growth. By leveraging these tools, organizations can stay competitive in an ever-evolving market while focusing on strategic, value-added activities. Embracing Salesforce automation is not just about efficiency but about enabling innovation and scalability in a fast-paced business environment.

Pranshu Goyal, Director of Products at Mirekta, states: “We envision DSM to be used by every small to a medium-sized organization dealing with bad data and want to get rid of duplicates easily with no cost. We have faced issues dealing with duplicates in our organization. That inspired us to make a solution that is not only simple to use but can be used widely to make the organization’s data clean to make them more efficient and productive. We want DSM to be a solution for every organization looking for duplicate management capability better than the Salesforce out-of-the-box solution with no additional cost.”