1 / 6

Project Intro: Research Knowledge Manager

Project Intro: Research Knowledge Manager. Jeff Buchmiller Business Research & Intelligence Group Alliance Data August 2013 jeff.buchmiller@alliancedata.com 214-494-3431. Company: Alliance Data. Customers get more products they want Customers save money Company performs better.

talia
Download Presentation

Project Intro: Research Knowledge Manager

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Project Intro: Research Knowledge Manager Jeff Buchmiller Business Research & Intelligence Group Alliance Data August 2013 jeff.buchmiller@alliancedata.com 214-494-3431

  2. Company: Alliance Data • Customers get more • products they want • Customers save money • Company performs better

  3. Function: Business Research & Intelligence • Some of My Job’s Goals • Enhance the Business Understanding model to cover how the contributions of our people and the investments we make in them impact the enterprise’s outcomes • Need a layer of abstraction to organize the knowledge represented in 1,000’s of documents and reports • My own special focus is on the workforce and organizational productivity aspects; each of my teammates has a different focus (economics, products & services, and marketing strategy), and we share the rest • Produce an Alliance Data "Workforce State of the Union" report • The prototypical example for how the project’s deliverable will be used – manages the data, information, & knowledge when it is too large to be held in my own head, helping me to pull from it quickly and easily • Provide research & analysis subject-matter expertise and education • Same as above, except very specific requests are handled on an ad hoc basis

  4. Project: Research Knowledge Manager • Repository of Knowledge • Documents • Reports from internal and external sources • News articles from the web • Miscellaneous data files • Videos • Images such as webinar screen shots • Email attachments • I myself have accumulated over 31,000 documents in the past few years

  5. Project: Research Knowledge Manager • Purpose of the Project • I use Google Desktop or Microsoft Indexing Service to index all the documents collected, then perform keyword searches to locate information needed to answer the question at hand. • It takes quite a while to locate all the relevant information, now that the document library has grown so large. • A significant portion of the time comes in having to open and read each document that my keyword searches “hit,” to evaluate whether it really does contain useful information. • Another significant consumption of time occurs because the number of documents that my searches “hit” is often large. • We need a better knowledge management tool that can help us get to the right information more quickly and reliably.

  6. Project: Research Knowledge Manager • Software Features • The deliverable is to be some form of desktop software that will index, tag, and search, at a minimum, the content of the documents. • There is just one user per installed instance on a desktop or laptop PC. • There needs to be a user interface for adding documents, tags, and other information into the system, and a user interface for performing searches. • We use Windows XP, Windows 7, or Windows 8. • Indexing could be accomplished similarly to existing technologies. There are different kinds of indexing available, including more semantic versions that “understand” the meaning of content and queries better than keyword indexing even attempts. There is a great opportunity to adopt and apply natural language processing and semantic web techniques to this problem. • Some conscious tagging by the user of content within documents can be extremely useful for later retrieval. • For example, there may be certain statements in documents that are related to “Big Data” and these can be tagged by the user, so that great search results specifically for the popular topic of Big Data are enabled, which may be impossible for any keyword search to accomplish.

More Related