IBM files a patent for a method, structure, and computer system for out-of-domain sentence detection in dialogue systems. The technology involves encoding and decoding text inputs to detect on-topic and off-topic sentences, minimizing and maximizing reconstruction errors accordingly. GlobalData’s report on International Business Machines gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on International Business Machines, M2M communication interfaces was a key innovation area identified from patents. International Business Machines's grant share as of January 2024 was 71%. Grant share is based on the ratio of number of grants to total number of patents.

Out-of-domain sentence detection in dialogue systems

Source: United States Patent and Trademark Office (USPTO). Credit: International Business Machines Corp

The patent application (Publication Number: US20240037331A1) describes a computer-implemented method for out-of-domain sentence detection. The method involves receiving on-topic and off-topic text inputs for a specific domain, encoding them into a latent space, decoding them, and then minimizing the reconstruction error for on-topic inputs while maximizing it for off-topic inputs. This process helps in determining whether a user dialogue is on-topic or off-topic based on the reconstruction error.

Furthermore, the patent application includes details about a computer program product and a computer system for out-of-domain sentence detection. These products and systems are designed to perform the method described above, utilizing sentence encoders, autoencoders, and loss functions to encode, decode, and analyze on-topic and off-topic text inputs. By assigning positive and negative factors for the loss functions, the system can effectively differentiate between on-topic and off-topic dialogues based on the reconstruction error. Overall, the technology outlined in the patent application aims to enhance the accuracy and efficiency of detecting out-of-domain sentences in various domains and topics.

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