IBM Data and AI Ideas Portal for Customers
This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (https://ideas.ibm.com).
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Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.
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There is highlight issue however related to searches that are searching in a specific field. E.g.
(metadata.dataroom_filename:"customer",metadata.dataroom_filename:("analysis"|"churn"))|("customer analysis"|"customer win"|"customer loss"|"customer churn"|"customer volume"|"top a customers")
i.e. lot of compound terms, but single terms are searched against filename only.
Here are matching snippets where you see that single words appear, in text snippets EVEN THOUGH they were search terms only against filename. Therefore user assumes that highlights are coming from the compound terms (e.g. "customer analysis") that are only partially matched.
Note that query does not have the term "customer" ever alone without being part of a compound term, except for filename search. However snippets show that customer, analysis match everywhere.
"text": [
"Industry applications of techniques to discover the factors that were most predictive One media company, for example, used machine learning of <em>customer</em> <em>churn</em> and identified the 2 percent of <em>customers</em> causing almost 20 percent of overall <em>churn</em>.",
"In these applications, machine learning helps classify <em>customers</em> or observations into groups for predicting value, behavior, risk, or other metrics. It can be used to triage <em>customer</em> service calls; to segment <em>customers</em> based on risk, <em>churn</em>, and purchasing patterns; to identify fraud and anomalies in banking and cybersecurity; and to diagnose diseases from scans, biopsies, and other data.",
"s Our <em>analysis</em> filters business use cases by impact potential and by data richness.",
"SOURCE: McKinsey Global Institute <em>analysis</em> Seven of those 18 capabilities are well -suited to being implemented through the use of machine learning (Exhibit20). The first striking observation is that almost all activities require capabilities that correlate with what machine learning can do.",
"It can be difficult for decision makers and <em>customers</em> to commit to insights that are generated in a non- transparent way, especially where those insights are counterintuitive. Medical use cases could fall into this category."
],
It turns out that there is a WDS defect related to the highlights. When a compound term is searched, it turns out that the one highlight is actually split into two, reversed in order and they are created by an incorrect line feed between the two words of a compound search term: see example above for WDS query="data capture" 4 last highlights are actually two highlights split into 2 and reversed in order!
"<em>capture</em> planning MEET IBM GBS Cloud Application Migration Services IBM Confidential 43 Asset work under way Cloud Innovate Thanks ",
"Advise on cloud I ensures IBM GBS Cloud Application Migration Services IBM Confidential - - - Microservices nt and Monitoring Secure cloud DevOps Migrate to cloud ions on the Cloud Integrated Cloud Platform Operations • Consistency of experience from IBM ensuring predictable outcomes • Assimilation of best practices & experiences ensuring superior output quality • Standard set of Tools facilitating <em>data</em>",
and
"<em>capture</em>, analysis and reporting • Efficiency that increases speed to value Ø Modernize for cloud Operations Guidelines Rationalize for cloud Cloud InnovateTM Methodology brings the IBM way to address Hybrid Cloud journey Cloud Innovate based on an end -to -end Method for cloud adoption meeting specific client demands Strategize / Mobilize Discovery & Analysis Design & Build ØP ops oa Applied To Secure",
"duplicate dete Data use pattern Minhash, LSH planning CTD, test scope partitioning detection Fine-grained Project simulation and risk assessment WBS and estimation * CRUD analysis qtr * * API candidate search Concept extraction, searchpatterns Test planning advisor Testing pattern advisor Mobile/web Coarse -grained practitioner support, Options text mining from catalog Transformation WBS and estimation <em>Data</em>"
I verified in the source document that the text indeed appears such that the above is true.