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2015-08-04
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2017-02-22
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When documents are locked by other applications such as DocuSign you cannot sign them or open them with this software. You are however able to sign them on that platform after creating a separate logon with DocuSign.
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Ability to send to sign is a huge time saver in getting contracts signed by sellers
The ability to edit PDF documents quickly and easily
What do you dislike?
When documents are locked by other applications such as DocuSign you cannot sign them or open them with this software. You are however able to sign them on that platform after creating a separate logon with DocuSign.
What problems are you solving with the product? What benefits have you realized?
Ability to send to sign is a huge time saver in getting contracts signed by sellers
2019-05-21
I have had a great experience thus far…
I have had a great experience thus far in my free trial. I have been able to merge documents to create a continuous flow, create signature stamps and fill out fillable pdfs' for my work. This is a great product!
2024-10-30
Need a dark background theme and to improve the highlighter color so that the text remains "clear" after highlighting! "Everything thing else is very good!"
2023-08-21
There are many template options to…
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2022-01-01
Great app, but even better customer service. I needed to cancel my membership for financial reasons, but I failed to do so before it renewed and my bank account was drafted. I submitted a request through the website for support and requested a refund. *** replied via email within an hour and had already issued the refund. Clearly they care about their customers, provide easy communication options and have fair policies in place.
2021-11-17
It works really good although saving…
It works really good although saving process for the PC is a bit bad because it doesn't save documents directly.
2020-05-08
Categorize Break Text Feature
The Categorize Break Text feature simplifies the way you manage and organize text-based data. This tool helps you break down lengthy text into categorized segments, making it easier to read and analyze. If you often deal with large bodies of text, this feature provides a practical solution.
Key Features
Breaks long text into manageable parts
Automatically categorizes segments based on keywords
User-friendly interface for easy navigation
Works seamlessly with various document formats
Supports custom categories for tailored organization
Potential Use Cases and Benefits
Improves readability for reports and articles
Aids in data analysis by organizing information systematically
Facilitates better collaboration by allowing team members to focus on specific segments
Saves time by reducing the effort needed to sift through extensive text
Enhances understanding of complex documents through clear categorization
This feature addresses the common problem of dealing with overwhelming amounts of text. By breaking down information into organized segments, you can quickly identify key points and make informed decisions. Whether you are a student, professional, or researcher, this tool empowers you to handle your text efficiently.
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How does text classification work?
Rule-based approaches classify text into organized groups by using a set of handcrafted linguistic rules. These rules instruct the system to use semantically relevant elements of a text to identify relevant categories based on its content. Each rule consists of an antecedent or pattern and a predicted category.
What are the classification of text?
What is Text Classification? Text classification models are used to categorize text into organized groups. Text is analyzed by a model and then the appropriate tags are applied based on the content. Machine learning models that can automatically apply tags for classification are known as classifiers.
What is meant by text classification?
Text classification (a.k.a. text categorization or text tagging) is the task of assigning a set of predefined categories to free-text. Text classifiers can be used to organize, structure, and categorize pretty much anything.
What is classification text structure?
Classification-division text structure is an organizational structure in which writers sort items or ideas into categories according to commonalities. It allows the author to take an overall idea and split it into parts for the purpose of providing clarity and description.
What is text classification in NLP?
Text classification also known as text tagging or text categorization is the process of categorizing text into organized groups. By using Natural Language Processing (NLP), text classifiers can automatically analyze text and then assign a set of predefined tags or categories based on its content.
What are examples of classification?
The definition of classifying is categorizing something or someone into a certain group or system based on certain characteristics. An example of classifying is assigning plants or animals into a kingdom and species. An example of classifying is designating some papers as “Secret” or “Confidential.”
How do classification algorithms work?
Classification is a technique where we categorize data into a given number of classes. The main goal of a classification problem is to identify the category/class to which a new data will fall under. ... Classifier: An algorithm that maps the input data to a specific category.
What are classification algorithms in machine learning?
Types of classification algorithms in Machine Learning. In machine learning and statistics, classification is a supervised learning approach in which the computer program learns from the data input given to it and then uses this learning to classify new observation.
What are classification algorithms used for in data science?
Classification is the process of predicting the class of given data points. Classes are sometimes called as targets/ labels or categories. Classification predictive modeling is the task of approximating a mapping function (f) from input variables (X) to discrete output variables (y).
What is ML classification?
In short Classification either predicts categorical class labels or classifies data (construct a model) based on the training set and the values (class labels) in classifying attributes and uses it in classifying new data. There are a number of classification models.
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