Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: CACM Article on DB/IR
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > CACM Article on DB/IR
Uncategorized

CACM Article on DB/IR

Daniel Tunkelang
Daniel Tunkelang
5 Min Read
SHARE

In my rush to finish writing my book this month, I haven’t had much time for reading. But I did notice an article in the April ‘09 issue of Communications of the ACM that caught my attention: “Database and Information-Retrieval Methods for Knowledge Discovery” (no subscription necessary for online access). I’m not sure what sort of IR system my brain uses, but that title certainly excited a lot of neurons!

It’s a worthwhile read, especially for people unfamiliar with the artificial dichotomy between database and information retrieval research. It’s a bit too academic for my taste–I would have liked to see at least some mention of the commercial efforts to bridge this gap between unstructured and structured information access (hint, hint). And of course there’s too much emphasis on ranking and nary a mention of interactive or exploratory interfaces.

But enough quibbling. Here are a few excerpts to when your appetite:

DB and IR are separate fields in computer science due to historical accident. Both investigate concepts, models, and computational methods for managing large amounts of complex information, though each began almost …

More Read

Your Movements Speak for Themselves: Space-Time Travel Data is Analytic Super-Food!
Predictive Modeling Skills: Expect to be Surprised
13 Tips for a Better Web Site
Social Media Expert Panel Discussion (Video)
False Relationships

In my rush to finish writing my book this month, I haven’t had much time for reading. But I did notice an article in the April ‘09 issue of Communications of the ACM that caught my attention: “Database and Information-Retrieval Methods for Knowledge Discovery” (no subscription necessary for online access). I’m not sure what sort of IR system my brain uses, but that title certainly excited a lot of neurons!

It’s a worthwhile read, especially for people unfamiliar with the artificial dichotomy between database and information retrieval research. It’s a bit too academic for my taste–I would have liked to see at least some mention of the commercial efforts to bridge this gap between unstructured and structured information access (hint, hint). And of course there’s too much emphasis on ranking and nary a mention of interactive or exploratory interfaces.

But enough quibbling. Here are a few excerpts to when your appetite:

DB and IR are separate fields in computer science due to historical accident. Both investigate concepts, models, and computational methods for managing large amounts of complex information, though each began almost 40 years ago with very different application areas as motivations and technology drivers; for DB it was accounting systems (such as online reservations and banking), and for IR it was library systems (such as bibliographic catalogs and patent collections). Moreover, these two directions and their related research communities emphasized very different aspects of information management; for DB it was data consistency, precise query processing, and efficiency, and for IR it was text understanding, statistical ranking models, and user satisfaction.
…
Structured and unstructured search conditions are combined in a single query, and the query results must be ranked. The queries must be evaluated over very large data sets that exhibit high update rates…A programmer can build such an application through two separate platforms—a DB system for the structured data and an IR search engine for the textual and fuzzy-matching issues. But this widely adopted approach is a challenge to application developers, as many tasks are not covered by the underlying platforms and must be addressed in the application code. An integrated DB/IR platform would greatly simplify development of the application and largely reduce the cost of maintaining and adapting it to future needs.
…
With a knowledge base that sublimates valuable content from the Web, we could address difficult questions beyond the capabilities of today’s keyword-based search engines. For example, a user might ask for a list of drugs that inhibit proteases and obtain a fairly comprehensive list of drugs for this HIV-relevant family of enzymes. Such advanced information requests are posed by knowledge workers, including scientists, students, journalists, historians, and market researchers. Although it is possible to find relevant answers, the process is laborious and time-consuming, as it often requires rephrasing queries and browsing through many potentially promising but ultimately useless result pages.

Enjoy!

Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Generative AI models
Thinking Machines At Work: How Generative AI Models Are Redefining Business Intelligence
Artificial Intelligence Business Intelligence Exclusive Infographic Machine Learning
image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

No Data, No Problem (Pt 2) – Your region/division/unit is not special.

7 Min Read

SIA: Lights, Camera, Action!

1 Min Read

How Do I Become a Data Scientist?

10 Min Read

3 Ways Manufacturing Companies Can Boost Efficiency with ERP

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?