Semantic Web: What Is The Killer App?

Written by Alex Iskold / January 9, 2008 10:22 PM / 1 Comments

The Semantic Web has been in the making for some time and people think it is nearing maturity. We have written about this trend extensively, with our two most notable posts being an analysis of the challenges of the classic bottom-up approach and the promise of the new top-down one. Regardless of how the Semantic Web will come about, for it to flourish it needs to hit the mainstream. There is no way that consumers will appreciate the elegance and mathematical soundness of RDF and OWL. People don't care about math, they care about utility and even more, about fun. What the Semantic Web needs, then, is a killer app.

Whatever it is, it needs to layer an understanding of semantics on top of a consumer application. The consumer application needs to be so cool and so viral that people will be open to learning that it is powered by semantic technologies. In that case, it will be possible to further market applications as Semantic Web apps. Consumers will understand that if one Semantic Web application has potential, so might others. In math, this is called proof by induction. In marketing this is called creating a market. In any case, it needs to be done.

In this post, we analyze several existing and potential applications of semantic technologies and look for the killer app.

Natual Language Understanding

Since the beginning, the Semantic Web has been associated with Artificial Intelligence. The idea of representing information in structured form so that computers can "understand it" and then solve complex problems was one of the keystones of the Semantic Web vision. The problem is that representing billions of existing web documents as RDF is a rather daunting, if not impossible task. An alternative would be to "teach" computers natural language. If an application could read the page the way we read it and interpret what it says, the annotations would not be necessary.

Natural language processing has been the Holy Grail of AI for awhile now. However, it is a very difficult problem, because humans are born with the innate ability to understand language and we learn it not in a vacuum, but in the context of life. Certainly if we could replicate that with computers, it would be amazing and it would be the killer app. The problem is that this is not on the horizon. The Semantic Web technologies of today are not able to represent natural language in its entirety, and this is not really even their goal. Even if we could represent each page completely, there is still the matter of interpreting structure into semantics, which is the magic that our brain does so well and so easily.

Genie In The Bottle

Related to natural language understanding, is another idea that is not on the horizon. John Markoff called it "the perfect vacation." I call it the "Genie in the Bottle" to illustrate the impossibility of this. There is a misunderstanding about the Semantic Web which is floating around, which equates the Semantic Web with ability to solve really hard problems. It is simply not true.

For example, if you go to a new travel agency and ask them to book the perfect vacation for you, the travel agent will not be able to do it, because she does not know you. In order to find the perfect vacation there needs to be constraints: where you've been before, who you are going with, what you like to do, what is your budget, etc. Finding the "perfect" vacation is not a one shot deal, it is a process, which leverages iteration and memory.

True, with the Semantic Web the information is structured, but it does not mean that the computer can necessarily solve complex problems. These are two completely different things. Just because you have a map, does not mean that you know the best way to get from point A to point B. Having a map is necessary, but it is not sufficient, you need the algorithm to find the best path. There is a big difference between asking what is the capital of France and what is the cheapest airfair today to fly from New York to Paris. And the even harder question is: Where should I go on vacation next? Computers are not going to give us an instant, perfect answer to this question anytime soon, if ever. Again, this would be the killer app, it is just not likely to happen.

Semantic Knowledge Databases

So what is realistic and possible today? The first in the list of growing applications are Semantic Knowledge Databases. The two examples that we will look at here are Freebase and Twine. While Freebase is focusing on building essentially a semantic equivalent of Wikipedia, and Twine is focused on a personal semantic database, both are databases, both focus on knowledge management, and both are Wikipedia-like. The advantage of these databases over Wikipedia is that they represent information in a structured way and support queries. To understand the difference, take a look at the Alicia Keys page on Freebase and on Wikipedia. At first glance they are very similar, but Freebase "knows" that Alicia Keys is a blues singer and it then knows other blues singers. For Wikipedia, blues is just another page, not a music genre. So Freebase can potentially answer a question of listing all blues singers, while Wikipedia can not.

This is certainly interesting but the question is will people care? Can the end consumer tell the difference? Unlikely. Today Wikipedia contains definitive references on a vast number of topics. Like Google, it is easy to search and find relevant information, and as a result, people are not likely to be in need of a better Wikipedia. With Twine the situation might prove to be different, because personal knowledge management is an important problem. The first question is: Are their enough people who want to be efficient in managing personal knowledge? I think the answer is increasingly likely to be "yes." And the second question is: Does knowing the semantics of knowledge help you build the best application? At the very least Twine has to beat del.icio.us bookmarks and ideally needs to do for personal knowledge management what Highrise is doing for CRM.

But beyond the execution, there is still another problem. For a semantic knowledge base to be the killer app it needs to ignite imagination and capture people's hearts and minds. This is not likely to happen. We appreciate libraries, we can not live without them, but we take them for granted. Knowledge has been commoditized thanks to Google, Wikipedia, and the blogosphere, and is perceived as abundant and unexciting. For this reason Semantic Databases are not likely to be the killer apps -- but they might become a stepping stone towards one.

Semantic Search

An early candidate for the killer app in the semantic web category was search. First Hakia and more recently Powerset marketed the idea that a semantic search engine, one that is based on the understanding of natural language, can beat Google. On top of having the pressure to deliver qualitatively better results, Semantic Search companies also have to, at least approximately, solve the problem of natural language understanding, which as we discussed earlier is a very difficult one.

Where things stand right now, it does not look like search is the killer app for semantics. The understanding of natural language does not seem to give you a noticeable edge in getting better search results. At least in the comparisons that we have performed earlier there is no major difference. The statistical algorithm deployed by Google is precise and good enough, which is why it has been the clear leader in web search for the past 8 years. To unseat Google will require more than incremental improvement in search, it will likely take a paradigm shift and the creation of a different web experience. Below, we discuss how "discovery" could possibly take a bite out of the pie, but as of now Google's algorithm remains good and strong.

Social Graph

After Tim Bernes-Lee posted his thoughts on the Social Graph, a discussion began on the web in which people wondered if the Social Graph is in fact the Semantic Web. This, however, is a gross misinterpretation of the post. The Social Graph is not the Semantic Web, nor is it the killer app of the Semantic Web. They are just two separate concepts. The confusion comes from the fact that they both are Mathematical Graphs or a Network. The underlying structure of both consists of nodes connected by links. Many things in the nature and society are networks, so it is not surprising that meaning and people fall into this category.

If anything, it is more correct to say that the Social Graph is a subset of the giant, all encompasing Semantic Web. Knowing how people are connected is important in order to solve the perfect vacation problem. After all, a perfect vacation should be taken together with perfect friends, right? But jokes aside, the Social Graph is an interesting and important trend for 2008, however, it is not really related to Semantic Web.

Shortcuts

Increasingly, we are seeing a new breed of Semantic Applications, which we generalize as shortcuts. This category includes SnapShots from Snap, BlueOrganizer and SmartLinks from AdaptiveBlue, Shortcuts from Yahoo!, and In-text search from Lingospot. What is common between all these technologies is that they leverage the simple semantics of the content to deliver additional information. In the case of Snap and AdaptiveBlue, the semantics is defined by the URL, while Yahoo! and Lingospot perform text analysis.

Regardless of the method, all of these technologies deliver related information via Ajax popups. That is, they leverage semantics to pull the information from the web. This is essentially discovery or reverse search. When the user is looking at a book there is a preview with a brief description and the cover image, when the user encounters a stock symbol he is presented with a stock chart, analysis and additional links to the company, when the user is looking at a music album there is a play button, and when the user encounters a movie there is an ability to watch the trailer in place. The shortcuts remove the need to search, instead, the related content from the web comes right into the page.

Today's shortcut technologies are simple and still in their infancy, but they are among the most successful examples of semantic applications. However, we can not call them the killer app for several reasons.

First, people perceive them as advertising, which is not the point. Snap certainly made an early push into ads, but this is not a representation of what these technologies will look like in the future. Second, in their current implementation, all of these technologies are utilities. For the same reason that people are not going to get emotional about personal knowledge management, they will not be emotional about shortcuts. Shortcuts will also be taken for granted.

Yet, shortcuts hold the most promise. With a few more iterations these technologies are going to get slicker and more precise. They will leverage content and micro-context to reduce the amount of search. They will become more personalized based on user behavior. And once this happens it will be a big deal.

Full Disclosure: Alex Iskold is the founder and CEO of AdaptiveBlue.

Conclusion

We are still waiting for the killer app for Semantic Web, something that can get viral and turn semantics into a marketing term. Problems like natural language understanding still remain difficult to solve, and the solutions do not appear to be on our horizon right now. It also appears that a semantic search engine, at least based on the ones we have seen to date, does not have a substantial advantage over Google. We are seeing the rise of early Semantic Knowledge Databases, but while we expect them to get better and more interesting, they are more likely to be the stepping stones to the killer app, rather than the app itself.

In the mean time, we are seeing the rise of shortcut technologies, which leverage the basic semantics of the content, like URL and simple context analysis, to deliver relevant information, links, and media directly into the page. While still very early, these technologies hold the most promise because they are simple and useful. We expect that the next generation of these technologies in conjunction with personalization will deliver an interesting alternative to search -- contextual discovery. We will discuss this alternative in more detail in a future post.

Now tell us what you think the killer app for Semantic Web will be? Which of these technologies do you think is the most promising?

MediaTrust PRESS RELEASE : MediaTrust Strengthens Management Team

NEW YORK CITY, January 9, 2008 –MediaTrust, Inc., an ecosystem of online media properties, today announced the addition of two vice presidents and a senior manager to its management team. Peter Ettenborough and Glenn Pagan both join MediaTrust as vice presidents of Business Development, MediaTrust Integrated Solutions Group (ISG) (http://www.mediatrust.com/isg.html). Chris Horne joins as senior product manager for MediaTrust’s relevance and social media technologies.

“As media and technology continues to converge, we continue to recruit experts from both sides of the business to ensure clients can trust us with all their online media needs,” MediaTrust CEO, Peter Bordes. “Each of these industry veterans joins MediaTrust with many years of experience delivering customer-centric solutions that move brands forward.”

Both Mr. Ettenborough and Mr. Pagan will be responsible for building custom performance-oriented online campaigns that optimize ROI for MediaTrust advertisers, agencies and publishers. Mr. Ettenborough, a sales professional with more than 20 years experience, most recently served as sales director for Prospectiv. In this position, he oversaw online lead generation for key accounts including Wal-Mart, General Mills, Gap, TJMaxx, Marshalls, Xerox, SC Johnson, Joann Stores, Kmart, Pitney Bowes, Hewlett-Packard and others. Prior to joining Prospectiv, Mr. Ettenborough worked for Reebok International, where he led key and strategic accounts for the apparel division. Mr. Ettenborough was also a founder and creator of Shreds Inc., a lifestyle apparel company which was later sold to Digital Domain.

Mr. Pagan is a highly experienced sales and marketing professional with more than 26 years experience in technology and media. Mr. Pagan has held senior roles at companies including IBM, Conde Nast Publications and Time Warner, Inc. Mr. Pagan has been involved with several startup companies, most notably NewsAlert, an online financial news and information search engine that Mr. Pagan helped grow to a $150M valuation. Mr. Pagan has developed and executed media strategies for some of the world’s biggest brands including Coca-Cola, Phillips Electronics, L’Oreal and BMW. Mr. Pagan serves on the board for The John Riggins Foundation, and serves as co-president of The Epic Theatre in New York.

Mr. Horne joins MediaTrust with more than a decade of product management and marketing experience within enterprise content management, relevance platforms and systems integration. Mr. Horne will oversee MediaTrust’s proprietary relevance engine and social media technologies that help companies more effectively monetize content on the Internet. Before joining MediaTrust, Mr. Horne worked at SeeBeyond Technology, where he was responsible for a range of activities including product management and marketing, analyst relations and competitive analysis. Mr. Horne has also worked for Documentum (now EMC) and CSC Consulting.

About MediaTrust
MediaTrust (www.mediatrust.com) is an ecosystem of online media properties. MediaTrust combines innovative interactive media and advertising technology with human service and expertise. Companies that choose MediaTrust benefit from relevant and intelligent online campaigns that deliver higher ROI and greater success in acquiring customers, creating brand awareness, generating sales and driving traffic.

MediaTrust comprises: Advaliant, a performance-based affiliate marketing network (www.advaliant.com); data management and Search and Social Media Optimization services; leading-edge media technologies; and the MediaTrust Integrated Solutions Group (ISG). The ISG is comprised of specialists that analyze customer needs and build custom performance-based campaigns that optimize returns for each advertiser and publisher.

What is the Recommender Industry?

GUEST COLUMN: What is the Recommender Industry?
Author: MSG Staff
By Dr. Rick Hangartner

Dr. Rick Hangartner, Chief Scientist, MyStrands, has nearly 30 years experience developing computing hardware and software in the aerospace, data communications, heavy-trucking, and supercomputing industries. Prior to joining MyStrands, he worked for seven years at Cray, Inc. developing high performance computing hardware and software.

No, the headline on this entry is not a careless grammatical error. Nor is the question really “What is the recommender market?” That would imply that “recommenders” are mature, well-defined technologies that deliver specific features and value to the online world. Emerging recommendation technologies are currently setting the standards for discovery and personalization in today’s social networking-dominated Web 2.0 environment-and the future of online social networking is all about discovery and personalization. While search engines help you find things you know you are looking for, discovery helps you find the rest.

If we accept that every business must make its case in 10 to 20 seconds on its Web site, then we are all but forced to admit that recommenders, more than anything else, represent the conceptual answer to the question, “How can I get that visitor/user/customer to realize that I offer something of value to him or her?”

Although venture capitalists and Web 2.0 users may find that claim to be just the tiresome excuse they need for hitting the “Back” button, the point is that a good argument can be made that unlike search engines, the recommender idea is a formal concept that has as many different concrete examples as there are separate market applications.

The recommender industry really is the business of pulling three components together into a system that helps a user-driven business convince their potential customers that they should stay for a while. These three elements include,

1) An effective model that relates the needs visitors have to what the business offers,

2) Quality data to build a model instance that relates specific needs to specific offerings, and

3) Unobtrusive means for easily and quickly determining an individual user’s needs.

Note that these three components are not quite as simple as “good (statistical) algorithms,” “a lot of data,” or “simple user interfaces.” In the coming years, defining an effective model will increasingly involve a scientific approach to understanding user needs and the market strategy of the business. Gathering quality data will require more sophisticated understanding of which data are actually relevant to the model. Devising means for characterizing an individual user’s needs will depend on a refined understanding of how people implicitly and explicitly signal needs that they themselves may not even fully understand.

In short, the recommender industry is the evolving business of building and deploying systems that reify some of the psychology of human economic transactions. What this means for the marketplace seems relatively clear: Search engines as we know them will never disappear. In the near term, search engines will increasingly incorporate simple recommender technologies to handle approximate queries (e.g., “You asked for this, and based on similar queries/behavior by others, you might be looking for this.”). But in the long term, the recommender industry will be larger, and recommender technologies will be more pervasive than the search industry and search technology as we know it.

Beyond that, some general themes about the future of the recommender industry that seem to be worth watching for include,

Multiple revenue models: Unlike search engines, which primarily are monetized through contextual ads of some form, recommender systems will be monetized in multiple ways. Recommender technology suppliers will continue to partner with customer businesses to derive revenue as a share of explicit sales increases directly accredited to the recommender system. In the longer term, recommender technology will increasingly enable business models, including advertising schemes, which could not exist without it. An implicit valuation for a specific application of a recommender system will be derived from the enabled economic activity.

Increasing focus on how users require change over time: In that recommender systems reify aspects of the psychology of economic transactions, there is an increasing appreciation for the probable value of responding to how economic behavior changes over time. This includes how an individual’s needs change over time and how the needs of the community evolve. The former can, in part, be accommodated by simply taking care to build a recommender system instance using data that is an adequate sampling of individuals whose needs are changing. Adapting to the latter may require recommender system models that explicitly incorporate features of how community needs to evolve.

New concepts of personalization: One of the recent trends in personalization is using information about an individual’s social network to better characterize that individual’s needs and interests. This may be just one aspect of a new concept of personalization that puts the focus not on delivering an isolating, customized experience to a person, but rather on connecting an individual with affinity communities who can provide information of value to that individual. Few people really want to be out there all alone. And for those explorers who do, they might, in reality, be hoping to build a community of like-minded souls or be waiting for others to catch up with them.

More than anything, the future of the recommender industry is a business that will continue to grow and become more sophisticated as the science of recommenders greatly develops to increasingly encompasses computer science, psychology, economics and cognitive science.

Strong Spend Ahead for E-Mail Marketing

JANUARY 8, 2008

But the tactic's humble rep could be hurting it.

E-mail marketing spending will grow to $2.1 billion in 2012 from $1.2 billion in 2007, according to JupiterResearch's "US E-mail Marketing Forecast, 2007 to 2012" report. “E-mail service providers have done a solid job of standardizing feedback loops with Internet service providers and are continuing to make needed improvements in e-mail delivery,” said David Daniels, vice president and research director at JupiterResearch.

“This will create better opportunities for e-mail marketing, although marketers will have to work harder to remain relevant in their communications with their intended audiences,” Mr. Daniels said.

JupiterResearch also said that spending on retention e-mail would more than double through 2012 and account for more than half of total e-mail marketing spending by then.

Acquisition e-mail marketing was pegged to grow more slowly, with sponsorships such as ad-supported newsletters accounting for most spending.

In its own calculations of e-mail marketing spending, eMarketer includes payments to e-mail service providers, list rental and the costs of in-house e-mail. eMarketer projects that e-mail marketing spending will creep up steadily, reaching $1.65 billion by 2011.

"E-mail marketing is effective, but spending is tempered by the somewhat but not entirely valid impression among many companies that e-mail is inexpensive marketing and that they therefore need not throw too much money at those programs," said David Hallerman, senior analyst at eMarketer.

Spending on e-mail marketing is also moderated by its own efficiency. Because e-mail is a low-cost medium, even relatively large increases in the number of commercial e-mails are not reflected in large spending increases.

Spending will jump by 5.1% in 2008, supported by marketing for both the national and local elections. Similarly, but to a lesser extent, marketing spending growth in 2010 will be boosted by election activity.

"US e-mail marketing spending in 2007 will reach nearly $1.5 billion," Mr. Hallerman said. "That is about $3.60 for e-mail marketing for every $1 that goes to e-mail advertising.

Wikia Search Is A Complete Letdown.

Wikia Search Is A Complete Letdown.
Many of us have waited a year as the Jimmy Wales hype machine promised a human powered search engine that could take on Google. Tonight that search engine launched at alpha.search.wikia.com, and it may be one of the biggest disappointments I’ve had the displeasure of reviewing.

Who Owns Your Social Data? You Do, Sort of

Who Owns Your Social Data? You Do, Sort of
Analysis: Scoble's banishment and reinstatement from Facebook revives the debate over who owns data entered on social sites.

Ad Houses Will Need to Be More Nimble

Clients Are Demanding
More and Better Use
Of Consumer Data, Web

By SUZANNE VRANICA
January 2, 2008; Page B3

The Web's emergence is forcing ad executives to succumb to marketers' demands that agencies reinvent how ads are created, and forgo their TV-centric approach. Clients are even calling for changes in the way ad firms are structured. But until now, few advertisers have spent more than 5% to 10% of their marketing budgets online. With the growth of online video and social networking, ad experts expect that percentage to jump significantly this year.

Gas Station TV's screens show programming from CBS and ESPN -- along with ads.

Softness in the economy also will likely drive more money to the Internet, which can be cheaper than other media and has a reach that is easier to measure, which is attractive to advertisers in slower times. Merrill Lynch predicts overall ad spending in the U.S. for 2008 will grow 2.3%, while the portion of that spending on the Web will increase 18%. Publicis Groupe's ZenithOptimedia says it expects the amount spent on Internet advertising to overtake spending on radio in 2008, and spending on magazines in 2010.

Amid this transformation of the ad industry, here are five trends to watch in 2008:

• New structure: The Web has fueled marketers' frustration with the lack of collaboration inside the ad holding companies that dominate the industry. Specifically, marketers want more cooperation between the executives who create ads for TV and newspapers and those who craft Web ads or perform less glamorous tasks such as researching consumer behavior.

Many advertisers complain that ad executives too often push agendas that will most help their own bottom lines and tend to favor certain types of media, such as TV. Advertisers want a "media-agnostic" approach, one that picks whatever medium is best for the ad campaign.

Some bigger marketers have taken matters into their own hands during the past year. Procter & Gamble, Dell and Johnson & Johnson each have tried -- working with ad holding companies -- to create new types of ad groups that blend different functions. In 2008, pressure from marketers on this issue is likely to intensify, forcing even more change in the way ad firms are structured.

• Screen wars: As advertisers find it harder to reach consumers in a fragmented media world, some are turning more often to the outdoors. Television screens are increasingly popping up in grocery and department-store aisles, elevators and even gas pumps -- all blaring clips of TV programs, accompanied by ads. Walt Disney's ESPN and CBS Corp. each have programming running on 20-inch liquid-crystal displays at pumps at gas stations around the country. Gas Station TV, which operates about 5,000 such screens in 300 cities, offers ads from marketers such as General Motors' Chevrolet and Sony. Last year, CBS inked a deal to have its programming also air in the waiting rooms of doctors' offices.

• House guest: Over the years, ad makers have tried various methods to learn about consumers, from focus groups to online polls. But many on Madison Avenue are skeptical of these methods, believing consumers don't always share their true feelings in those types of traditional settings. So a growing number of ad agencies are expected to try a different approach: having researchers spend long periods of time with consumers to find out more about how they live.

Some have already tried this. When devising a new ad for J.C. Penney last year, Saatchi & Saatchi sent staffers to hang out with more than 50 women for several days. They helped the women clean their houses, carpool, cook dinner and shop. Rather than pepper them with questions, the agency employees simply observed the women's behavior and emotions. Their research became the basis of a new ad campaign; the commercials have won praise from Madison Avenue's creative community.

"If you want to understand how a lion hunts, you don't go to the zoo -- you go to the jungle," said Sandy Thompson, global head of strategic planning for Saatchi, which is owned by Publicis Groupe.

• Green backlash: Corporate America latched onto environmental marketing last year, as big companies spent millions of ad dollars promoting their products and services as eco-friendly. Some people in the ad business are predicting a backlash this year from consumers who question whether companies are living up to their promises. "Marketers will be more intensely scrutinized for their green efforts -- those that don't hold up will be called out via blogs and elsewhere online, ultimately leading to consumer skepticism," said Greg Stern, chief executive of the ad firm Butler, Shine, Stern & Partners.

• The antisocial movement: Privacy issues, combined with the fact that consumers have only so much free time, could damp the boom in social networking on the Web. "Nobody has 5,000 real friends," says Tim Hanlon, senior vice president of Denuo Group, a media and advertising consulting firm owned by Publicis. "At the end of the day it just becomes one big cauldron of noise." For marketers, he says, that will mean the sites will be much more effective as a consumer-research tool than as a venue to peddle products.

Write to Suzanne Vranica at