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Showing posts with the label semantic tagging

Why Do We Use Entity Extraction :Text Analysis Software ?

  Entity Extraction is a part of text analysis. The most important question is why we need text analysis software and what's the meaning of Entity Extraction? It is quite questionable for the general public why we have to use Text analysis Software to check words or texts, they think for educated people it's very easy to analyze words, contexts, or any reviews from customers. So in the end, they decide that we don't need any advanced software for screening customers’ reviews.  Entity Extraction Software: Artificial intelligence is here to help us make and create things faster than usual. With the help of Artificial intelligence and machine learning our software company created one of the best Text Analysis software. Text analysis  software helps us to analyze data, texts, messages, reviews more thoroughly and helps to detect customers' inner feelings or thoughts. Our AI-based text analysis software detects subject emotions of long paragraphs, website texts, contents, an...

Get a brief and deep idea about Entity Extraction

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  Modern-day tasks need modern techniques. We have to work smarter rather than giving time, energy to only one thing and that might be expensive too.  Machine learning techniques are included in many new technologies to make them more user-friendly and easier for general people. Text analysis is invented by using machine learning to make text analyzing and interpreting easy for people. Text analysis helps to interpret the subjective analysis of texts, data, paragraphs, chat, and many more. When we encounter a huge chunk of unstructured data it's not possible for a single human to analyze all data. Also, there must be some inaccuracies. And we know very well in any business matter and professional work we can't afford to make a single mistake. Entity Extraction is a part of your business Named Entity Extraction  is a part of text analysis. Entity Extraction, as per the name it recognizes names, entities, countries, tags in different terms. It helps to recognize every singl...

WHAT'S THE USE OF NAMED ENTITY EXTRACTION?

Entity extraction  or Named entity extraction is a part of the Natural Language Processing technique. Language processing is an advanced technique of text analysis. Analyzing text and finding the exact emotions and meaning behind that it's now handling artificial intelligence. NowadaysText analysis software is invented by many IT companies using Machine learning, Natural Language processing, and most importantly artificial intelligence. What is Named Entity Extraction ? Named Entity recognition extracts or identifies some particular words from a huge data set and it helps to categorize such as Organization, Expressions, Time, Person, Place, etc. So we use named entity recognition to find or categorize data from websites, articles, and even social media platforms. With the vast amount of advancements of  NER( Named Entity Recognition)  and implementing machine learning, we can analyze text and extract from unstructured data like Twitter, email,sns feed. When it's difficult...

Smart and fast way for abusive language detection

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  The Internet becomes the main purpose of our life to do anything. From our school, office work to communicating with family members via different apps, sending money, the Internet is needed. We have already entered the online world from where we can't escape. The growing number of social media sites and users makes researchers think about how to make social communication places more transparent and clearer. We are very much aware that hate comments, offensive language, triggering images, and sensitive topics which can hurt people are continuously used by anonymous people on social media. Importance of detecting abusive language is growing on the basis of growing audiences in the online world. Abusive language detection tool helps to prevent bullying behavior in social networking platforms as you see twitter the most popular social communicating site using this technique to provide more friendly interactions among users. Triggering images or offensive languages are automatically ...

Choose best Free online sentiment analysis Tool

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  In this online world where we all are working 24*7 hours on the Internet, analyzing everything is now part of work. Despite having SSL on the website, we need to verify everything before and after publishing our website. If you have a blog site or online shopping store you need to know the content's impact on customers. Reviewing customers' thoughts is the only option to exposure of your own sites.   A free online sentiment analysis  tool is a perfect tool to describe and analyze sentiments. With the help of advanced technology like Machine learning, natural language processing, text mining, and many more.   Sentiment analysis is an advanced way to review the subjective thought of texts with the help of text mining. With the increase of blogs, review sites-commerce websites we need to prioritize only meaningful texts neither violating rules or hate comments. Free   Online Sentiment analysis is the best way to optimize people's emotions and determine the emotio...

Text Tagging in Natural Language Processing

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Text tagging is the technique of automatically adding tags or remarks to different bits of lengthy text as part of the comprehensive data gathering for analytics. Text tagging is a more thorough form of stratification than categorization, and it may provide deeper insight. Named entity extraction  is a classic definition of text tagging or semantic tagging. A batch of complex text can be processed using this extraction tool to evaluate the names of individuals, brands, organizations, locations, or dates. The correlation and sequence of conversations between the mentioned entities might be determined using this method. Natural Language Processing Text Tagging  can be performed fully automated, although computer software that conducts auto-tagging is also available. When the majority of the key criteria are known, some applications essentially employ rules and word lists to classify output suitably. However, more complicated systems (based on various cases) may leverage advanc...