Factoids from Best Paper Awards in Computer Science
January 6, 2021
I noted “Best Paper Awards in Computer Science Since 1996.” The year caught my attention because that was the point in time at which software stagnation gained traction. See “The Great Software Stagnation” for the argument.
The Best Papers tally represents awards issued to the “best papers”. Hats off to the compiler Jeff Huang and his sources and helpers.
I zipped through the listings which contained dozens upon dozens of papers I knew absolutely zero about. I will probably be pushing up daisies before I work through these write ups.
I pulled out several observations which answered questions of interest to me.
First, the data illustrate the long tail thing. Stated another way, the data reveal that if an expert wants to win a prestigious award, it matters which institution issues one’s paycheck:
Second, what are the most prestigious “names” to which one should apply for employment in computer science? Here’s the list of the top 25. The others are interesting but not the Broadway stars of the digital world:
| 1 | Microsoft | 56.4 |
| 2 | University of Washington | 50.5 |
| 3 | Carnegie Mellon University | 47.1 |
| 4 | Stanford University | 43.3 |
| 5 | Massachusetts Institute of Technology | 40.2 |
| 6 | University of California, Berkeley | 29.2 |
| 7 | University of Michigan | 20.6 |
| 8 | University of Illinois at Urbana–Champaign | 18.5 |
| 9 | Cornell University | 17.4 |
| 10 | 16.8 | |
| 11 | University of Toronto | 15.8 |
| 12 | University of Texas at Austin | 14.5 |
| 13 | IBM | 13.7 |
| 14 | University of British Columbia | 12.4 |
| 15 | University of Massachusetts Amherst | 11.2 |
| 16 | Georgia Institute of Technology | 10.3 |
| 17 | École Polytechnique Fédérale de Lausanne | 10.1 |
| 18 | University of Oxford | 9.6 |
| 19 | University of California, Irvine | 9.4 |
| 20 | Princeton University | 9.1 |
| 21 | University of Maryland | 8.9 |
| 22 | University of California, San Diego | 8.7 |
| 23 | University of Cambridge | 8.6 |
| 24 | University of Wisconsin–Madison | 8 |
| 25 | Yahoo | 7.9 |
Note that Microsoft, the once proud Death Star of the North, is number one. For comparison, the Google is number 10. But the delta in average “bests” is an intriguing 39.6 papers. The ever innovative IBM is number 13, and the estimable Yahoo Oath Verizon confection is number 25.
I did not spot a Chinese University. A quick scan of the authors reveals that quite a few Chinese wizards labor in the research vineyards at these research-oriented institutions. Short of manual counting and analysis of names, I decided to to calculate authors by nationality. I think that’s a good task for you, gentle reader.
What about search as a research topic in this pool? I used a couple of online text analysis tools like Writewords, a tool on my system, and the Madeintext service. The counts varied slightly, which is standard operating procedure for counting tools like these. The 10 most frequently used words in the titles of the award winning papers are:
| data 63 times |
| based 56 times |
| learning 53 times |
| using 49 times |
| design 45 times |
| analysis 38 times |
| software 36 times |
| time 36 times |
| search 35 times |
| Web 30 times |
The surprise is that “search” was, based on my analysis of the counts I used, was the ninth most popular word in the papers’ titles. Who knew? Almost as surprising was “social” ranking a miserable 46th. Search, it seems, remains an area of interest. Now if that interest can be transformed into sustainable revenue and sufficient profit to fund research, bug fixes, and enhancements — life would be better in my opinion.
Stephen E Arnold, January 5, 2020
Sinequa: A Logical Leap
December 21, 2020
The French have contributed significantly to logic. One may not agree with the precepts of Peter Abelard, the enlightened René Descartes, or the mathiness of Jean-Yves Girard. A rational observer of the disciplines of search and retrieval may want to inspect the reasoning of “How Apple’s Pending Search Engine Hints at a Rise in Enterprise Search.”
The jumping off point for this essay is the vaporware emitted by heavy breathing thumb typers that Apple will roll out a Web search engine. The idea is an interesting one, but, as I write this, Apple is busy with a number of tasks. But vaporware is a proven fungible among those engaged in enterprise search. The idea of finding just the information one needs when working in a dynamic company is a bit like looking for the end of a rainbow. One can see it; therefore, there must be an end. Even better, mothers have informed their precocious progeny that there is a pot of gold at the terminus.
What can one do with the assumption that an Apple Web search engine will manifest itself?
The answer is probably one which will set a number of French logicians spinning in their graves.
According to the write up from an “expert” at the French enterprise search firm Sinequa:
So, if Apple is spending (most likely) billions of dollars recreating a tool that effortlessly finds us the global sum of human knowledge, then isn’t it about time we improve the tools that knowledge workers have to do their jobs?
That’s quite a leap, particularly for a discipline which dates from the pre-STAIRS era. But from a company founded in 2002, the leap is nothing out of the ordinary.
But enterprise search is a big job; for example:
The complication is that enterprise data is more heterogeneous in nature than internet data, which is homogeneous by comparison. As a result, enterprise data tends to reside in silos, so if we need to find a document, we can narrow down where we look to a couple of places – for instance, in our email or on a particular SharePoint. However. further complication arises when we don’t know where to look – or worse still, we don’t know what we’re looking for. A siloed approach works fairly well but at some point, we start to lose track of where to look. According to recent Sinequa research, knowledge workers currently have to access an average of around six different systems when looking for information – that’s potentially six individual searches you need to make to find something.
And why has enterprise search as a discipline failed to deliver exactly what an employee needs to do his or her job at a particular point in time?
That’s a good question which the logical confection does not address. No problem. Vendors of enterprise search have dodged the question for more than half a century.
Here’s how the essary nails down its stunning analysis:
It’s only a matter of time before enterprise search reaches a similar tipping point. There will be a time when the silos become too many or the time taken to search them becomes too great. The question is whether the reason for enterprise to take search seriously is because a lack of search is seen as an existential threat, or an opportunity to differentiate.
Okay, 50 years and counting.
Do you hear that buzzing sound? I surmise that it is René Descartes trying to contact Jacque Ellul to discuss how French logic fell off the wine cart.
My hunch is that Messrs. Descartes and Ellul will realize that providing access to information in response to a particular business need is a digital version of running toward the end of the rainbow. Some exercise, d’accord, but the journey may end in disappointment.
Par for the course for a company whose product pricing begins at $0.01 if Sourceforge is to be believed. Yep, $0.01. Logical? Sure. It’s marketing consistent with the hundreds of companies which have flogged enterprise search for decades.
Rainbows. Pots of gold. Yep.
Stephen E Arnold, December 20, 2020
Smart Software Can Find Different Points of View
December 18, 2020
All news outlets are dominated by one-sided rhetorics and dance to ratings and political tunes. The goal of news outlets is to sensationalize everything to generate profit and promote political agendas. It leaves viewers wanting more from news outlets, such as unbiased information. It is a sad time, indeed, when individuals long for news outlets of yesteryears because they had more diverse perspectives.
With today’s advanced technology one would think there would be a news search engine that rounded by articles of varying perspectives so individuals could come to their own opinions. Apparently such a search engine exists: https://articlefinder.org
Article Finder’s has a minimalist UI and uses colors to make people think about Google. The premise is simple:
“People will view the same story in different ways based on their priors. It’s important to understand how others view the same event to better understand how they think. Article Finder allows you to find articles of the same story from different sources so you can gain a holistic picture.”
After conducting a few searches, Article Finder does retrieve different articles about the same topics. It relies on a customizable Google search. The search results are returned in an organized list that states the title and news source. The minimalist style decreases distraction.
However, I wonder if Article Finder is any different from a regular Google news search? Google offers news from multiple sources and even customizable options through Google profiles. Article Finder serves a purpose but it seems unnecessary unless they add something new.
Whitney Grace, December 18, 2020
Amazon Uses Googley Phrase Which Also Was Mostly Marketing Hoo Hah
December 17, 2020
You may not remember, but I do. Like yesterday. I wrote an analysis for the late, highly regarded financial services firm and contract bridge epicenter BearStearns. The document was published more than a decade ago. Two things happened. Google immediately rolled out a special event to announce universal search. I heard that the name morphed into unified search and then federated search among some Googlers. The idea is that a user runs a query and expects the content of which he or she is aware will be in the results. Ho ho ho. The merrie search elves know that even at the mighty Google one must search silos of data. Universal, unified, federated. That’s like a Dark Web vendor posting 1 800 YOU WISH as the customer support number for bogus contraband.
Imagine my surprise when I noted this Amazon post:
Universal, unified, whatever. I find it fascinating how search related terminology comes into vogue and falls out of favor only to return in a weird but actually identifiable Kondratiev waves. Examples include:
- Inference (nifty but there was a search vendor called Inference now essentially forgotten)
- Boolean which several vendors have resurrected after thumbtypers declared the method dead
- indexing now creeping back into favor after metadata and enrichment have not moved the needle for jargon recycling.
Yep, unified. Much better than “federated”, of course. Remember Vivisimo? I sort of do, but IBM repositioned it as some whizzy part of Watson. Is search at AWS or anywhere for that matter what the user expects. Ho ho ho say the merrie search elves. Ho ho ho. That’s a good one.
Stephen E Arnold, December 16, 2020
Enterprise Search Art
December 8, 2020
I noted Pixeltrue’s collection of Covid art. Take a look. Very good work. But — there is a but when Beyond Search looks at Covid art. One of the Beyond Search team revised the captions for several of the images so that each reflects more accurately what we call “search syndrome.”
Headache: The direct result of a free Web search results page.
Plus, choking when reviewing irrelevant results:
Gag, hack, hack.
Stephen E Arnold, December 8, 2020
Microsoft Bing Edge Shopping Reinvented. What?
November 24, 2020
I read “Reinventing Online Shopping on Microsoft Edge.” I like the word “reinventing.” It implies that online shopping is not using Amazon.com. Much to Google’s chagrin, the Bezos bulldozer has become the number one destination for those in the lower 48 who are looking for products. Six out of 10 shopping “journeys” begin online, according to Sleeknote. The same outfit reports that nearly half of US online commerce sales end up at Amazon. An outfit called Moz reports:
With 54 percent of product searches now taking place on Amazon, it’s time to take it seriously as the world’s largest search engine for e-commerce. In fact, if we exclude YouTube as part of Google, Amazon is technically the second largest search engine in the world.
So what about shopping on Microsoft Edge?
I ran this query on Microsoft Edge for AMZ 5700 video card. Here’s what I saw on November 22, 2020:
I ran the same query on Firefox. Here’s what I saw:
Both are different. The write up about reinventing shopping asserts that there are true blue, accidental, and incidental shoppers. That’s MBA think in action. The write up continues:
we [Microsoft] came up with a native-to-browser design framework that tailors shopping assistance to prioritize different information depending on the shopper’s stage in their journey. We determine what stage a person is at based on what kind of page they’re on.
Microsoft points out:
As you design your experiences, think about relying on a consistent UI paradigm that is both familiar and always available to the user. In our case, the UI framework leverages the URL bar, or address bar, in Edge as a quick one-touch anchor for shopping assistance. The URL bar is where people expect things relevant to the current webpage to show up — and we are extending the same model to surface optimized shopping insights. [Emphasis added]
I want to point out:
- I see two different user interfaces: One looks like a Google jumble and the other looks like eBay
- I don’t look for shopping information in the url bar. The url bar is where I want to see — wait for it, please — the url
- Neither interface benefits from little pictures. I am searching for a specific thing and I want a link to a relevant page, not a jazzed up “report.”
Amazon’s shopping is certainly not perfect, but I don’t have to figure out why the display looks different in different browsers or what’s is available.
MBA alert: Amazon and Google have much more traffic than Bing when it comes to shopping. You can check your traffic data for verification, not look in the url bar for an experience. This reality check will verify that blue is the sadness of shopping data analysis, the accidental weirdness Microsoft result pages present to a human shopper, and the incidental effort varying graphical interfaces display.
Stephen E Arnold, November 23, 2020
Enterprise Search: Still Crazy after All These Years
November 20, 2020
This is not old wine in new bottles. This is wine in those weird clay jars with the nifty moniker “amphora” filled with Oak Leaf Vineyards Sauvignon Blanc White Wine. Cough, cough.
CMS Wire gets it correct when it declares, “Scanning and Selecting Enterprise Search Results: Not as Easy as it Looks.” The article doesn’t even approach the formation of a query—finding the right wording then tweaking filters and facets to produce a manageable list. Here we are only looking at the next step. Though the task seems simple on its surface—scan a list of results and select the most relevant ones—writer Martin White explains why it is not so straightforward.
First is scanning results. Users’ perceptual speed differs, so for some folks (like those who are dyslexic, for example) the process can be so tedious as to make searching pointless. White tells us that inconvenient fact is often overlooked in the discussion of search functionality. Also under-considered is the issue of snippet length. A bit of research has been performed, but it involved web pages, which are themselves more easily scanned and assessed than content found in enterprise databases. Those documents are often several hundred pages long, so ranking algorithms often have trouble picking out a helpful snippet. Some platforms serve up a text sequence that contains the query term, others create computer-generated summaries of documents, and others reproduce the first few lines of each document. Each of these approaches is imperfect. Still others produce a thumbnail of a whole page that contains the search term, and that probably helps many users. However, there are accessibility problems with that method.
White concludes:
“We know from recent research that people may make different decisions from the information they perceive initially as relevant based on their expertise. Equally, most search metrics are based around the notional relevance of the results being presented in response to a query. If the true value of relevance cannot be well judged from the snippet, that calls any metrics associated with query performance (especially precision) into question.
“There are no easy solutions to the issues raised in this column. In the quest for achieving an acceptable user experience the points to consider are:
*Are the techniques used by the search application to create snippets appropriate to the types of content being searched?
*Can the format of snippets be customized by the user?
*How easy is it to scan and assess results from a federated search?
“In the final analysis, it doesn’t matter how sophisticated the search technology is (in terms of semantic analysis, etc.). What matters is if the user can make an informed judgment of which piece of content in the results serves their information requirement, reinforces their trust in the application and maintains the highest possible level of overall search satisfaction.”
Sigh. It seems the more developers work on enterprise search, the more complicated it is to effectively operate. The field has been at it for 50 years, and is still trying to deliver something useful. Still crazy after all these years too.
PS. Our esteemed check writer (Stephen E Arnold) wrote a book about enterprise search with the author of the source document. No wonder this essay seemed weirdly familiar. I had to proofread what turned out to be prose that made the Oak Leaf stuff welcome at the end of an editing day. Cough, cough, eeep.
Cynthia Murrell, November 20, 2020
Survey Says Data Governance Is Important. But What Is Data Governance?
November 20, 2020
Here’s what the Google says governance means: The action or manner of governing. Okay, but what exactly is governing. Google says: Having authority to conduct the policy, actions, and affairs of a state, organization, or people.
Okay, now let’s add the magic word “data,” which is a plural, not a single thing. (That’s what datum means, right?)
Google says: Facts and statistics collected together for reference or analysis.
Let’s put the information together, shall we?
An organization uses authority to conduct policy, actions and affairs to deal with facts and statistics for reference or analysis.
Why care? The answer is found in “Businesses Positive about Data Governance but Still Struggle with Privacy Concerns.”
Okay, now we have linked dealing with information and privacy. This is getting interesting or is it? I go with the “not interesting,” but let’s plod forward in the write up.
A vendor of search and retrieval software sponsored a research project conducted by Standard & Poor 451 Research. Note: That report is titled “Pathfinder Report Market Intelligence: Information Driven Compliance and Insight. Two Sides of the Same Coin.” I am not sure about the “coin” metaphor, compliance, insight, and pathfinding. But no one ever accused me of understanding mid-tier consulting firms, sponsored research, and 18 year old vendors of proprietary search and retrieval software.
The 451 outfit tapped its pool of “survey responders” and discovered:
72 percent of enterprises believe data governance is an enabler of business value rather than a cost center.
Okay, that’s a lot of enterprises, assuming the sample was statistically valid, the questions not shaped, and the data analysis of the survey responses was performed on the up and up. But sponsored research is different from the often wonky academic research churned out by professors and work-from-home students. That’s better, right?
I learned:
- One in four organizations have more than 50 distinct data silos
- 37 per cent of respondents say having relevant information automatically displayed, when the team needs it, would benefit them the most in the pursuit of automation.
- Budget, privacy issues, and expertise are barriers.
How does one deal with data silos, which I assume is “governance”? How does one deal with security? Privacy? How does an enterprise search company cope with the assorted sixes and sevens of data in an organization; for example, tweets, encrypted messages, images, geospatial data, videos, and information which must be kept isolated from the grubby “let’s federate information” crowd? (Why must some data be isolated? Find an attorney. Ask her what happens if information in a legal matter is out of her span of control.)
What’s the net net of the mid-tier consulting outfit’s report? Here it is:
Success requires alignment of business objectives by looking for common-denominator requirements across business units.
Let me be clear: Enterprise search is not the solution to problems with an “authority to conduct policy, actions and affairs to deal with facts and statistics for reference or analysis.”
Enterprise search is information retrieval, data governance no matter how much a marketer wishes it were. Enterprise search vendors have been struggling for relevance because Lucene/Solr are good enough and users want information to address right now business issues. Library style lists of stuff to read or look up may not ring the chimes of a thumb typing user.
Want the full report? Go here. Please, keep marketing and governance separate. Statistics 101 offered some useful guidelines. Some, however, did not pay attention. You will have to register. Marketing is still marketing.
Stephen E Arnold, November 20, 2020
Expert System Has Embraced the AI Revolution
November 19, 2020
It’s official. Expert System S.p. A. (Italy) is now Expert.ai. I know because the firm’s Web site displays this message:
Expert System has moved along a business path like one of those Amalfi coast cliff side roads: Breathtaking turns, chilling confrontations with other vehicles, and a lack of guard rails.
Repositioning a big rig is a thrill for sure.
The company’s tag line is:
It’s time to make all data actionable.
Yep, “all.” Even video, encrypted messages among employees, and confidential compensation data? Sure, “all.”
Plus, the firm has tweaked its description of its focus to assert:
Expert.ai is the premier artificial intelligence platform for language understanding. Its unique hybrid approach to NL combines symbolic human-like comprehension and machine learning to transform language-intensive processes into practical knowledge, providing the insight required to improve decision making throughout organizations.
Vendors of search and content processing widgets are responding to today’s business environment with marketing. Expert System was founded in 1989 in Modena, Italy.
Premier too.
Stephen E Arnold, November 19, 2020
Palantir Technologies: Once Secretive Company Explains What It Is Not
November 17, 2020
I enjoy once-secretive companies explaining what they are not. A good example of this type of re-formation is “Palantir Is Not a Data Company (Palantir Explained, #1).” The headline makes it clear to me that there will be additional “we are not” essays coming down the intelware pike. The first installment of what a stealth company communicated incorrectly it seems is:
Palantir is not a data company and not a data aggregator.
The write up wants to differentiate from a company like Datminr or Oracle BlueKai and similar firms. These outfits suck up information and then sell access to those data.
Palantir Technologies is not in that “data” business. The company processes the data its clients have, license, or to which the clients link in an appropriate manner.
The essay makes clear that Palantir is a “software company.” That’s true. Much of the software is open source or crafted to perform specific functions which customers pay Palantir to effectuate. (There are partners and integrators who perform other work for Palantir licensees. Most of these companies keep a low profile and do not advertise their Palantir goodness.
Several observations:
- Palantir is a hybrid outfit; that is, it combines open source software, custom code, and consulting to generate revenue
- Partners and integrators contribute expertise and software shims to allow a licensee obtain a desire output from the Palantir system
- Much of Palantir “runs” on cloud services; for example, Amazon Web Services.
Now that Palantir is a publicly traded company, the once stealthy firm which operated as a start up for more than a decade has to demonstrate that it is avoiding some of the public relations pitfalls for intelware and policeware vendors in the public eye.
How difficult is this task? Quite challenging in my opinion.
I am looking forward to the second installment of explaining Palantir.
Stephen E Arnold, November 17, 2020
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