What we are looking for?Something similar to https://try.expert.ai/document-classification/iptc but with custom taxonomies Are custom taxonomies only possible with Studio?Based on my readings, it appears custom taxonomies can only be defined using Studio.The thread above is a few months old, is it still true? Is there a documentation / guide on how to use the Studio? Basically, we want to take the results once the content / document is processed on given taxonomies, use it to provide appropriate suggestions to the end user. This could be easier with a REST API, not sure how Studio could help here. Any pointers?
Hi,would anyone know how to retrieve segmentation results from a document analysis that have been created by a studio rules set?I can see the segments in studio analysis results in the results file <testfile>.ctx.json: In the documentation of nlapi/edge (https://docs.expert.ai/nlapi/latest/), though, I can’t find any explanation on how to retrieve segment boundaries.Thanks for any hint!
I have frequently noticed that when I upload documents to the Platform, often the docs are treated and rejected as not being English. For example, in the attached screenshot, the very short document is rejected because the engine considers the NL to be French when it is clearly English: “Adoptive cruise control allows excessive acceleration when vehicle detection clears.” Is there a configuration that I should change to remedy this? Is there a way to override the engine so this doesn’t happen? Thanks!
Thanks for reading. I’m wondering why, when I manually annotate a document in Platform, my annotation is treated as an FN. I would think that, because I hand curated the annotation, it would be considered a TP an FN means an incorrect indication of the absence of a condition when it is actually present. I’m referring to 1) a condition is present and 2) I approve it by annotating, yet the system seems to override my decision-making process. If I annotate a term or phrase and I’ve ensured it’s in the right class, I expect a green TP. I have attached an example where I found a corporate entity, “ONEOK,” that I manually annotated because it belongs to a certain class. However, rather than being indicated by green, as a TP, it is purple. Since this is factored into Experiment scores, it seems like a) I am being penalized for taking the time to manually annotate a document and b) the machine is overriding what I have done as an SME.I hope this makes sense. Perhaps I need a better under
Hi Community.I’m brand new to Studio and working through the intro videos. Currently stuck at step 2 on building rules “Use the KEYWORD attribute in your categorization rule.” https://docs.expert.ai/studio/latest/101/work-with-c-rules/I’ve made a simple rule that looks for a keyword in my text document and Built the module - which completes successfully. As soon as try to analyse the document I get the error below (see image)Analyze Document XXX.txt failed ( - Rules not compiled)There is no where I can find guidance on compiling the rules. Any suggestions as I’m obviously missing something?Many thanks for any help!
The data labeling process for machine learning datasets is vital for the performance of the model. First of all, it would be essential to ascertain the type of data labeling; check if you are looking for data labeling at scale or want a dataset prepared for a pilot project.Data labeling can be done manually if there are a few rows and the data is textual; to be used for testing the functioning of basic machine learning models. There are several open-source data annotation tools available for usage, which can be used for sorting data. If your data labeling needs are diverse then you will need to find a suitable data labeling tool.However, if both data and the model with business objectives require professional-grade handling with right data labeling tools then approaching a data labeling solution provider is a good idea. Data labeling companies provide different kinds of annotation such as Bounding Box, Semantic Segmentation, Landmarking, Polygon, Polyline, 3D Cuboid, LIDAR Annotation.
Outsourcing is one of the most important methods for organizations to become more efficient and successful, both financially and in terms of human resources. Beyond the traditional outsourcing functions, today’s businesses are looking at the sheer amount of recorded audio and video content to see how they can outsource and turn it into something more valuable.Outsourcing transcriptions is a natural next step for organizations that capture audio and video from meetings, interviews, podcasts, webinars, and other relevant content. When you transcribe a video to text, it becomes instantaneously searchable, legible, and ready to publish or share in any format.Here are a few interesting reasons to consider outsourcing transcribing services if you haven’t already:1. Refocus on your companyIt’s never a bad idea to focus on your major company operations, goals, and strategies. Every firm, in some form, has limited resources, and every department manager has limited time and attention daily. Out
Match Supplier Invoice product data with Customer Purchase product data and customer Purchase receipt
Hi Bmunz,As discussed previously. I would like to learn how Expert.ai studio rules can that we create helps to match both supplier and purchase invoices along with Purchase receipts in a 3Combination way.First step I would like to learn is Does Expert.ai reads the PDF document from OCR as it is a demo requirement.If it does how are you guys do it at Expert.ai and if its not how you resolve these kind of issuesSecond Step would be building the rules in StudioHere are the attached supplier, Purchase order and purchase receipt invoice in a PDF and PNG format.Here Sanitarium Dairy company is SupplierColes is purchasing the order as you can see it with the product SKU’sAlso there is a Coles purchase receipt with 2 pages and I want to know if we can match the three by building semantics around the product.It would be appreciated if you can help me as we are going to present a demo in 2 weeks.Cheers,Venkat.
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