Natural Language Processing: Tomorrow and Yesterday

October 31, 2017

I read “Will Natural Language Processing Change Search as We Know It?” The write up is by a search specialist who, I believe, worked at Convera. The Search Technologies’ Web site asserts:

He was the architect and inventor of RetrievalWare, a ground-breaking natural-language based statistical text search engine which he started in 1989 and grew to $50 million in annual sales worldwide. RetrievalWare is now owned by Microsoft Corporation.

I think Fast Search acquired a portion of Convera. When Microsoft purchased Fast Search, the Convera technology was part of the deal. When Convera faded, one rumor I captured in 2007 was that some of the Convera technology was used by Ntent, formed as the result of a merger between Convera Corporation and Firstlight ERA. If accurate, the history of Convera is fascinating with Excalibur, ConQuest, and Allen & Co. in the mix.

In the “Will Natural Language Processing Change Search As We Know It” blog post, I noted these points:

  • Intranets incorporating NLP, semantic search and AI can fuel chatbots as well as end-to-end question-answering systems that live on top of search. It is a truly semantic extension to the search box with far-reaching implications for all types of search.
  • With NLP, enterprise knowledge contained in paper documentation can be encoded in a machine-readable format so the machine can read, process and understand it enough to formulate an intelligent response.
  • it’s good to know about established tool sets and methodologies for developing and creating effective solutions for use cases like technical support. But like all development projects, take care to create the tools based on mimicking the responses of actual human domain experts. Otherwise, you may run into the proverbial development problem of “garbage in, garbage out” which has plagued many such expert system initiatives.

Mr. Nelson is painting a reasonable picture about the narrow use of widely touted technologies. In fact, the promise of NLP has been part of enterprise search marketing for decades.

What I found interesting was the Convera document called “Accurate Search: What a Concept, published by Convera in 2002. I noted this passage on page 4 of the document:

Concept Search capitalizes on the richness of language, with its multiple term meanings, and transforms it from a problem into an advantage. RetrievalWare performs natural language processing and search term expansion to paraphrase queries, enabling retrieval of documents that contain the specific concepts requested rather than just the words typed during the query while also taking advantage of its semantic richness to rank documents in results lists. RetrievalWare’s powerful pattern search abilities overcome common errors in both content and queries, resulting in greater recall and user satisfaction.

I find the shift from a broad solution to a more narrow solution interesting. In the span of 15 years, the technology of search seems to be struggling to deliver.

Perhaps consulting and engineering services are needed to make search “work”? Contrast search with mobile phone technology. Progress has been evident. For search, success narrows to improving “documentation” and “customer support.”

Has anyone tried to reach PayPal’s customer support or United Airlines’ customer support? Try it. United was at one time a “customer” of Convera’s. From my point of view, United Airlines’ customer service has remained about the same over the last decade or two.

Enterprise search, broad or narrow, remains a challenge for marketers and users in my opinion. NLP, I assume, has arrived after a long journey. For a free profile of Convera, check out this link.

Stephen E Arnold, October 31, 2017

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