登录查看更多内容

What are the best practices for improving contract searchability with text analysis?

由人工智能和领英社区提供技术支持

If you deal with contracts regularly, you know how challenging it can be to find the right information quickly and accurately. Whether you need to review terms, obligations, risks, or compliance issues, you don't want to waste time and resources on manual searches that can miss important details or lead to errors. That's why text analysis can be a powerful tool for improving contract searchability and management. Text analysis is the process of extracting meaningful insights from unstructured text data using natural language processing (NLP) and machine learning techniques. In this article, we'll share some of the best practices for applying text analysis to your contracts and how it can benefit your business.

在这篇协作文章中查找专家回答

由社区从 5 条内容中精选。了解更多

1 Define your goals and use cases

Before you start using text analysis for your contracts, you need to have a clear idea of what you want to achieve and how you will use the results. For instance, you may want to use text analysis to automate contract classification and tagging based on topics, types, or categories; extract key information and metadata such as parties, dates, clauses, or values; compare and contrast different contracts or versions to identify similarities, differences, or inconsistencies; analyze contract performance, risk, or compliance based on predefined criteria or indicators; and generate summaries, reports, or insights from your contract data. By defining your goals and use cases, you can select the most suitable text analysis methods and tools for your needs and measure your outcomes.

添加您的观点

Noah Alfaro

Purchasing Agent, Software Developer, Consultant, Leader
举报内容
In the case of automating contract classification, a good starting point is to check for the presence of keywords. Build a collection of keywords for each contract you would like to detect. Start with common section headings that are present in most contracts such as "ENTIRE AGREEMENT", "PRICE AND PAYMENT", "TERMINATION", and so forth. Certain agreements will contain certain requirements and keywords. Identifying and mapping them to a contract classification and a set of requirements will save lots of time when contract volume is high. In construction, for example, this may be achieved with JavaScript in Bluebeam Revu, a common program used to view and edit construction PDFs, contracts, and plans.

已翻译

赞

2 Prepare your data and documents

Before applying text analysis, you need to prepare your data and documents carefully to ensure the accuracy and reliability of your results. This includes collecting and organizing contracts in a centralized repository, converting them into a standard format such as PDF, DOCX, or TXT, cleaning and normalizing the data by removing duplicates or errors, enriching it with additional sources or metadata for context and detail, and segmenting it into smaller units such as sentences, paragraphs, or sections. By taking these steps, your text analysis can process and understand your contracts more effectively and efficiently.

添加您的观点

Noah Alfaro

Purchasing Agent, Software Developer, Consultant, Leader
(已编辑)
举报内容
In order to do any automation, you will need your inputs and outputs to be similar. They should all be of the same format and quality. I prefer a contract to be in PDF that can be parsed, not a scan of a printout where it loses parsability. The input should be converted into an intermediate format such as a .txt file, where is can be easily fed to another process for parsing, cleaning, and enrichment. After it is parsed and the automations have yielded their insights, you can convert the data/report back into the standard output of your choosing.

已翻译

赞

3 Choose the right text analysis tools and techniques

Text analysis is a broad and complex field that involves various tools and techniques for performing different tasks and functions. Depending on your goals and use cases, you may need to use keyword extraction to identify the most relevant words or phrases in your contracts, topic modeling to group them into clusters based on common themes, named entity recognition to locate and label specific entities, sentiment analysis to determine the tone or emotion expressed in them, text summarization to create a concise summary, text comparison to measure the similarity or difference between two or more contracts, or text generation to produce new text. When selecting the right text analysis tools and techniques, you should take into account factors such as data size, quality, and complexity; desired output and format; available resources and budget; and technical skills and expertise.

添加您的观点

Noah Alfaro

Purchasing Agent, Software Developer, Consultant, Leader
举报内容
It is difficult to create a one-size-fits-all analysis technique. It will need to be tailored to your situation. In many cases, the sentiment of a contract is irrelevant unless it is a unique agreement. High volume contract workflows are usually dealing with templated agreements, and in this case, change to the template is more important than the tone of the contract. Version analysis should take precedence over sentiment in these cases, and so one should pick a tool that specializes in version tracking. On the other hand, if your workflow is based on contracts of an individual nature, the sentiment is a good metric to track.

已翻译

赞

4 Evaluate and optimize your text analysis results

After applying text analysis to your contracts, you need to evaluate and optimize the results to ensure they meet your expectations and requirements. To assess the quality and usefulness of your text analysis results, you can use accuracy, precision, recall, F1-score, and feedback metrics. Through evaluation and optimization, you can identify any issues or gaps, improve your text analysis performance, and enhance your contract searchability and management. Moreover, this process will help you determine how well your text analysis results match the actual or expected values, as well as how specific and relevant they are to your query or goal. Finally, it will provide insight into how complete and comprehensive your text analysis results are to your query or goal and how they are perceived by users or stakeholders.

添加您的观点

5 Leverage your text analysis insights and benefits

Finally, you need to leverage your text analysis insights and benefits to achieve your goals and use cases. Text analysis can provide you with valuable and actionable information that can help you save time and money by reducing manual work and increasing efficiency, as well as improving quality and consistency by minimizing errors and enhancing accuracy. Moreover, it can mitigate risk and ensure compliance by detecting and resolving potential issues or conflicts. Text analysis can also enhance decision making and strategy by discovering and applying best practices and opportunities, while increasing customer satisfaction and loyalty by delivering better and faster services and solutions. Ultimately, leveraging your text analysis insights and benefits can give you a competitive edge in the market, creating more value for your business and customers.

添加您的观点

Jonathan Johnson-Swagel

AWS | GenAI & MLOps Leader | Driving AI-Powered Contract Solutions | Former Uber Tech Operations Lead | Lean Six Sigma Expert in Cloud Process Automation & Transformation
举报内容
Enhancing contract searchability with text analysis is a critical practice in modern contract management. Standardizing contract terminology and categorizing contracts make it easier for text analysis tools to identify and extract key information accurately, while robust OCR technology aids in metadata extraction. Utilizing full-text search capabilities and maintaining regular updates to the text analysis system further improves search accuracy. Harnessing the power of text analysis tools, organizations can significantly streamline contract searchability, saving time and resources, reducing errors, and enhancing decision-making to achieve the goals re: reduce time & errors, mitigate risk, and enhance customer satisfaction across the board.

已翻译

赞

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

Jonathan Johnson-Swagel

AWS | GenAI & MLOps Leader | Driving AI-Powered Contract Solutions | Former Uber Tech Operations Lead | Lean Six Sigma Expert in Cloud Process Automation & Transformation
(已编辑)
举报内容
In your process, think early about implementing text analysis: 1. Ensure that your contracts use standardized terminology and are categorized systematically, simplifying the process of information extraction through text analysis. 2. The incorporation of advanced tools, such as AI-driven solutions, empowers efficient metadata extraction, contributing significantly to accurate search results. 3. Utilizing full-text search capabilities allows you to scan through entire contracts, ensuring that no crucial details are overlooked. 4. Keep the text analysis system updated regularly. You can streamline contract searchability, saving time and resources, and minimizing the risk of missing vital contract information during the review process.

已翻译

赞

Contract Management

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

What are the best practices for improving contract searchability with text analysis?

1

2

3

4

5

6

1 Define your goals and use cases

2 Prepare your data and documents

3 Choose the right text analysis tools and techniques

4 Evaluate and optimize your text analysis results

5 Leverage your text analysis insights and benefits

6 Here’s what else to consider

Contract Management

给文章评分

感谢您的反馈

更多Contract Management相关文章

更多相关阅读内容