At its Google I/O conference Wednesday, company execs introduced “conversational search” capabilities. As Google implements its “hotwords,” users will no longer need to click the microphone in the search bar to start using voice recognition. All users have to do is say, “OK, Google,” and then speak commands. Google relies on natural language processing to figure out what users want to do and then serves up results.

Combine that with Google search’s ability to go beyond serving up graphs and other data in response to user questions and actually weave in additional information Google thinks users are looking for. For example, if you search for China, Google will not only show changes in population over the decades, but it will also graph the countries  China’s population is often compared to — India and the United States.

This is possible as Google keeps expanding knowledge graph, which now has more than 570 million entities, such as people, places and things, said Amit Singhal, a senior vice president and Google Fellow.

Coming soon: More knowledgeable searches

The knowledge graph operates with searches in English and eight other languages. Starting today, Singhal said, it will be  available in simplified Chinese, traditional Chinese, Polish and Turkish.

Google is also integrating personal data into searches in Chrome on desktops and laptops, which makes loads of sense. Flight reservations, restaurant reservations, package deliveries, and other user-generated information can be rapidly pulled up in the familiar interface of Google search results. That could put an end to going through emails of paper for this sort of information, saving users time.

Johanna Wright, vice president of search and assist for mobile at Google. Source: Janko Roettgers

Google has provoked lots of buzz and some concerns with its Google Now feature on mobile devices. The application will soon allow users to set reminders — to call someone, buy something — and expect them to occur only at the right time.

Parlaying personal and general data

Johanna Wright, vice president of search and assist for mobile at Google, took some of these new and upcoming features for a spin. As an example, she said she wanted to plan a day trip to Santa Cruz, Calif. So she said “OK, Google” — bringing Google to attention — “show me pictures of the Santa Cruz boardwalk.” Up came multiple pictures in a horizontal bar at the top of search results. She wanted to know the length of the trip and said, “OK, Google, how far is it from here?” Google figured out that “here” was her current location, in San Francisco, and “there” was Santa Cruz and displayed a map and spoke back that the drive would take an hour and 21 minutes.

She then asked seafood restaurants and got a list. Then she asked Google a tough question: “How tall do you have to be to ride the Giant Dipper?” Google came back with, “You must be at least 4 feet 3 inches tall to ride the Giant Dipper. “Nice,” she said. “Looks like my son can go on.”

On a mobile device, Wright also directed Google Now to send a quick email based on her voice commands, which happened right away, and set a reminder for her to call a friend when she arrives in New York on a business trip. FInally, she was able to tell Google to show the pictures she made during a previous trip. And about 16 pictures came right up.

The combination of personal data with more traditional search data is a logical next step for Google, which has no shortage of either. While Google Now has critics, it could become more popular with these new features. And how could people — investors included — question Google’s innovations in search, its core product. The voice recognition capabilities make searching still more intuitive and set the bar still higher for everyone else.

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While there is something undeniably creepy about the Google Now service, I have to admit that it is also very useful — so much so that I couldn’t imagine going on a trip without it. I’m already imagining how it and other kinds of “anticipatory data” services (including Google News updates) might work through Google Glass.

Useful information when you need it

It’s not that Google Now is really all that revolutionary, in the sense of being surprising or magical or having whiz-bang special effects: it just collects a broad range of information about you and your activity from your search history, your calendar, your email, web services you are signed into, and so on, and then uses that to show you information that is relevant to what you are doing or where you happen to be (Google recently introduced it for iOS as well as Android).

In a way, that could be part of the reason Google Now is so appealing — it doesn’t try to impress you, it just works silently in the background, in more or less the way you would expect it to. That in itself is something to be grateful for.

The first time I noticed myself depending on it (or at least noticing how useful it was), came when I was getting ready for my flight to Italy: sliding upwards from the home button on the Nexus 4 showed a series of Google Now “cards,” and the first one said that my flight had been delayed by an hour. Since I was panicking at that point about how much I still had to do before leaving for the airport, that information was incredibly helpful. I could take a bit more time and relax.

Meanwhile, the second Google Now card showed the traffic on the highway and told me that I should probably give myself more time than usual to get to the airport — and when I got closer to the time of my departure, a third card showed my boarding pass information, including boarding time and the gate number (Google Now got that info from my calendar, but it also supports scannable boarding passes for a limited number of airlines).

Not revolutionary, but evolutionary

Again, none of this information was specific to Google Now, or derived magically by Google search trickery: I could have easily found out about my flight being delayed by using a service like FlightStats, or by checking the website for the airline or the airport itself — and I could have checked the traffic on any number of sites. But the point is that doing these things would take time, and I was already pressed for time. Seeing it all displayed in front of me in a simple way, without me having to do anything, was exactly the kind of thing a virtual assistant is good for.

Google Now continued to perform this kind of function while I was travelling (once I got a local SIM card, of course, so that I wouldn’t get robbed by my carrier for roaming charges). It told me that my connecting flight in Munich was on time, which allowed me to prepare for possibly not making my connection — and once I arrived in Italy, it informed me of the weather, the traffic from the airport in Rome, and also showed me photos of nearby sights that I might want to visit.

These latter aspects were also very useful for someone visiting a foreign country: I didn’t have much use for them while I was at home, but they instantly became much more important when I was travelling. Like the flight information or traffic, I could have found that content myself by doing a web search — but it was much handier to have it displayed for me automatically. And I started to imagine what it might be like to simply look at something like the Colosseum with Google Glass and have information about it appear in front of my eyes. Geeky? Yes. But also hugely useful.

The privacy tradeoff is worth it

The part that clearly disturbs some people about Google Now is the data collection that is involved in making it work: the tracking of your web searches, your calendar appointments, your location via GPS, the photos you have posted, the flights you are preparing to take, and so on. There’s no question that this is invasive — and some users will undoubtedly decide that it’s not worth the tradeoff, and choose to keep the information to themselves. I think the benefits outweigh the disadvantages.

Are there ways Google could use this information that I might not like? Of course there are. But I trust that Google is aware enough of the dangers — both legal and commercial — of engaging in that kind of behavior that they will avoid it. While some may choose to see Google’s ambitions in this area as evil, I think the company’s goal remains the same: to provide services that encourage users to spend more time on the internet and produce more data that improves Google’s search and/or advertising algorithms. And I am okay with that.

In return for providing some anonymized data and behavior patterns, I get access to a personalized assistant that is not only more unobtrusive than any human version would be, but is also faster and completely free. That’s a pretty good bargain.

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The case followed complaints by Microsoft and others over Google’s treatment of rivals’ web services in its search results. These companies argue that Google favors its own services, which are not clearly marked as such, and also that it unfairly locks advertisers onto its platform and scrapes content from third-party search and comparison sites without consent.

A recent leak outlined the terms of the proposed settlement deal, but here’s the official version:

To address these concerns, Google offers for a period of 5 years to:

(i) – label promoted links to its own specialised search services so that users can distinguish them from natural web search results,
- clearly separate these promoted links from other web search results by clear graphical features (such as a frame), and
- display links to three rival specialised search services close to its own services, in a place that is clearly visible to users,

(ii) – offer all websites the option to opt-out from the use of all their content in Google’s specialised search services, while ensuring that any opt-out does not unduly affect the ranking of those web sites in Google’s general web search results,
- offer all specialised search web sites that focus on product search or local search the option to mark certain categories of information in such a way that such information is not indexed or used by Google,
- provide newspaper publishers with a mechanism allowing them to control on a web page per web page basis the display of their content in Google News,

(iii) no longer include in its agreements with publishers any written or unwritten obligations that would require them to source online search advertisements exclusively from Google, and

(iv) no longer impose obligations that would prevent advertisers from managing search advertising campaigns across competing advertising platforms.

Authorities in the U.S. more-or-less cleared Google over similar complaints, but it’s important to note that Google’s share of the search market there is around 67 percent, whereas in the E.U, it’s around 90 percent. This gives it stronger market power in Europe, and forces the regulators’ hand somewhat (as do local laws).

A Q&A document, which outlines the Commission’s concerns in detail, points out that “it does not seem likely that another web search service will replace [Google] as European users’ web search service of choice.”

“In this context, it is important for the Commission to intervene in order to ensure that Google’s prominent market position in web search does not affect the possibility for other competitors to innovate in neighbouring markets, including in the long-term,” the document states.

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“Search should be a critical part of your architecture,” he told attendees. It is a system building block for any large problem you’re trying to solve that requires a ranked set of results. And it doesn’t have to be just text search, it can be for any type of search, he said.

Thinking beyond traditional search features, like keyword search, will help businesses solve those problems more easily too. And it lets organizations bring in many differing kinds of data sources and more effectively combine them.

And organizations that keep records of how people are using search to access their data, they have the best current view into the quality of their data.

His main message was to give search another look. “There have been interesting changes in the way we can model relevance in the search engine,” he said. “If you’ve dealt with last-generation search technology, you should revisit this because there’s a lot more capabilities here.”

Check out the rest of our Structure:Data 2013 live coverage here, and a video embed of the session follows below:

A transcription of the video follows on the next page

Go to page 2 (of 2) on GigaOM .

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The launch is timely, considering Punchfork is shutting down its API at the end of the month after it was bought by Pinterest. Several sites and apps tap Punchfork’s recipe content and search capabilities – for instance, Punchfork powered Evernote Food’s Explore Recipes feature – so it will soon be looking for an alternative.

Yummly’s API, though, isn’t just a Punchfork clone, said Brian Witlin, the search portal’s new head of platform and mobile. Punchfork aggregated content from member food blogs and organized its recipes on social principles. Yummly on the other hand delves deep into the ingredients, cooking methods and the science behind each of the recipes it categorizes. It teases nutritional data out of its recipes, and its algorithms can even infer if a particular dish will be spicy, bitter or sweet. Users, for instance, can use Yummly to search specifically for low-fat or gluten-free dish options or find meals guaranteed to blow the socks off even the most jaded spice fiend.

“There are so many ways we can slice and dice the data we have,” Witlin said. “We plan to offer even more options in the next couple of months.” Yummly, however, doesn’t yet have tools to replace the social context Punchfork provides its customers, but Witlin said it’s in the works.

Initially customers most likely will use the Yummly API to provide more generic recipe content and search in their sites and apps. One of Yummly’s early API testers, search engine DuckDuckGo, uses the API to answer specific recipe queries, basically extending Yummly’s search portal onto its own site.

But developers will eventually be able to tap into Yummly’s technology to make their recipe and cooking services smarter. For instance recipe aggregation apps such as Evernote, Paprika and BigOven store recipes scrapped from all over the web, most of them drawn from the same sites Yummly categorizes. Those companies could use Yummly’s API to organize their customers personal recipe boxes into much more useful categories.

Instead of sorting your recipe library by generic soup, salad, meat and poultry labels, you could sort them by calorie level, salt use, level of spiciness or any of hundreds of different categories that aren’t spelled out in the recipes themselves.

Of course, Yummly can only sort the recipes it catalogs so any recipe you enter manually or from a site Yummly doesn’t aggregate won’t benefit from the API. But Witlin said Yummly eventually plans to amp up its recipe parsing technology so it will immediately scan any new recipe it encounters, adding it to its database.  When that happens, there won’t be any recipe Yummly can’t categorize, Witlin said.

Featured image courtesy of Flickr user lilivanili

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Google’s search algorithms are excellent at surfacing relevant content for basic keyword style head queries, but when we search for something specific using a long tail query, the answers aren’t consistently relevant. I would submit that this isn’t so much an issue with Google’s search algorithm as it is a content problem; that is, a large number of content sources that attempt to service long tail queries simply do a poor job of it. For Google to improve its search relevance for long tail queries – which it must, as those continue to become a huge chunk of its searches – it should integrate a high-quality QnA service like Quora with its search.

Google’s long tail problem

To better understand the differences between the two types of search, and the dilemma Google now faces, do a quick search using any or all of the following, pretty straightforward long tail queries and check the quality of search results:

“diet plan for diabetics and high blood pressure”
“how to get rid of acne”
“what do turtles eat as pets”
“how to train your parrot to talk”
“important things to consider before purchasing a house”

You will quickly discover that the results are mostly identical or slightly rehashed versions of other articles scraped from multiple sites across the web, many of them originating from content farms like Demand Media and Associated Content. Those sources are among many that specialize in trying to corner the market on servicing long tail queries. However they all suffer from two major problems:

Poor quality The army of low-paid freelancers who manufacture the “content” for these sites get paid essentially by volume. They are almost never experts in a given topic (or even passingly familiar, one could argue). They simply crank out 500-word article as quickly as possible so that these networks can embed three adsense ads in between and then move on to the next topic.

Bias toward popular keywords Despite intending to service long tail queries, in fact many of these services tend to produce content around keywords that are popular enough that they can reliably generate advertising revenue.

A source of reliable long tail query content

Clearly there is a demand for reliable long tail query content queries. Now consider a practical one like “how to get a passport faster,” and how massively helpful it would be to get the answer from a person who has actually gone through the process, rather than the person who designed the process. Wouldn’t it be logical for Google to implement a source of content that is produced by generally passionate, informed people –  a source like Quora?

Unlike Wikipedia, which is best at answering head queries, Quora is all about long tail. So integrating Quora with search would provide Google’s users more reliable and useful results for long tail queries. It would also contribute to a virtuous cycle by allowing users to help produce reliable content, too, as searches prompt further contextual content that may need answering. This will help Google get knowledge from content sources (such as those who contribute to Wikipedia) who do not own a website but have valuable knowledge.

Here’s a rough mockup of a Google search results page for the long tail query “diet plan for hypertension and diabetes” but with Quora integrated:

As another example, for a more task-based query like “how to file taxes,” you might also end up with relevant contextual content in the right pane of the search results:

• How do I calculate taxes?
• What is the last date to file taxes?
• What are the tax changes for 2013?
• What are the important things I should know before I file my taxes?
• What is the best software to file taxes?

Integrating Quora will enable Google to serve far more relevant answers for a much broader range of queries even though a smaller percentage of people will be actively producing the content. And it’s worth noting that in the process, Google will be effectively replacing dollars other networks pay to content churners with upvotes and follows to passionate users instead (talk about virtuous cycles!).

This is social search, where content will be produced in the context of social, but consumed in the context of search.

Narendra Reddy is chief product officer for the educational software developer Wignite. Follow him on Twitter @naren.

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The changes apply to Android and iOS versions of Twitter as well as the mobile browser version. The updates include a change to the discover tab, which will now include suggestions for both users and tweets all at once; search results that show all content in one stream rather than dividing up by users and tweets; and a tweaked connect tab that now defaults to all interactions rather than just mentions.

The full explanation of the changes are available in Twitter’s blog post updated on Wednesday morning.

Getting users to take advantage of the discover tab has been an ongoing goal for Twitter, as is improving its search function, which has undergone significant changes to become what it is today. The content created by Twitter users is ideal for building a useful search engine, much as Facebook wants to do, and the company has been moving in that direction this year.

Thumbnail image courtesy of Shutterstock user maminez

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For an example of what this means in practice, look no further than a new Tumblr blog started by London-based programmer Tom Scott, entitled “Actual Facebook Graph Searches.” This also sounds somewhat dry and academic, until you take a closer look at some of the things that Facebook makes it trivially easy to search for — things like “Islamic men interested in men who live in Tehran, Iran” (where homosexuality is a crime punishable by death) or “family members of people who live in China and like Falun Gong,” the latter being a religious group whose members are routinely persecuted.

Many of these searches may be figments of Tom Scott’s over-active imagination (at least for now) but the fact is that Facebook’s graph search makes them relatively easy to conduct. Dave Morin, a former Facebook executive who left to start the mobile social network Path, has pointed out that the company has had this kind of interest-graph powered search for some time — and this kind of targeting based on “likes” and interests, friends and followed pages, etc. has been available in a different form for advertisers. But it is far more robust and more public now.

It’s not about privacy, but the end of obscurity

In a FAQ on the blog, Scott says he’s not trying to make any deep arguments about privacy, and his Tumblr blog is subtitled: “Don’t worry, we’ll all be used to this in a few weeks’ time.” But it’s still worth thinking about the implications of Facebook’s graph search, especially given the fact that many people don’t seem to appreciate the nuances of the network’s privacy settings — something that Facebook doesn’t really make simple or easy to figure out. Even CEO Mark Zuckerberg’s sister Randi was recently blindsided by them, so what chance do the rest of us have?

In a recent piece in The Atlantic, philosophy professor Evan Selinger and his co-author Woodrow Hartzog argued that in many ways it’s not really helpful to talk about privacy, which is a vague concept in a world of real-time information, “frictionless sharing” and “data exhaust” (the information we give off as we move around the internet, often without realizing it). Instead, they argue that what we are really losing is the protection of obscurity — in the sense that information which was technically public before but difficult to find provided a form of privacy through obscurity:

“Obscurity is created through a combination of factors. Being invisible to search engines increases obscurity. So does using privacy settings and pseudonyms. Disclosing information in coded ways that only a limited audience will grasp enhances obscurity, too. Since few online disclosures are truly confidential or highly publicized, the lion’s share of communication on the social web falls along the expansive continuum of obscurity: a range that runs from completely hidden to totally obvious.”

As Selinger notes, the recent publication of a map of New York state’s registered gun owners made much the same point as Scott’s examples of disturbing Facebook graph searches. The information about who has a gun permit was public by default in New York when the map was published (although a new law has been proposed that would make it private) but it was difficult to collect and so hardly anyone bothered. Other kinds of information are also technically public — government databases and so on — but difficult or impossible to extract useful data from.

Clicks you may not even remember are being analyzed

Of course, the same thing was the case with much of the world’s information before Google came along, and we had to learn to adjust to the fact “the internet never forgets,” and that the information you posted online years ago (or information that was posted about you by others) without really thinking of the consequences can come back to haunt you. But Facebook has taken that to a whole new level of intimacy because much of what occurs there seems so ephemeral: a “like,” a follow, a click — things you might not even remember doing.

While they may seem ephemeral, each of these can be as permanent as anything else on the internet, and just as public, unless you can master the intricacies of what Facebook lets you hide and what it doesn’t (and as Scott notes in his FAQ, you probably shouldn’t rely on that anyway). As Megan Garber of The Atlantic points out in a post, the social network is essentially constructing a virtual version of you out of all those signals — a version that is categorized by all of your activities and interests, some of which may be harmless and some of which may not.

It may seem absurd that someone might say they “like” racism, or that anyone would actually search for that behavior and make use of it somehow. But if we have learned anything from the era of big data, it is that if the information is available — as dirty or questionable as it might be — someone is going to make use of it, and not always in the way you would like them to.

Post and thumbnail images courtesy of Flickr user Alan Cleaver and Tom Scott

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The launch, which Om Malik covered from Menlo Park through our live blog, is a direct dig at Google by taking advantage of all of the personal content and data Facebook has amassed to create a more individualized version of search. (As Om noted, it’s also remarkably similar to Path’s recent search product, called Path Moments, in that it takes a more thematic approach to information users are searching for focused on people, events, or photos.)

The company explained the thinking behind Graph Search in a full press release on its website Tuesday, including how it plans to incorporate aspects of privacy into the product.

Graph Search and web search are very different. Web search is designed to take a set of keywords (for example: “hip hop”) and provide the best possible results that match those keywords. With Graph Search you combine phrases (for example: “my friends in New York who like Jay-Z”) to get that set of people, places, photos or other content that’s been shared on Facebook. We believe they have very different uses.

Another big difference from web search is that every piece of content on Facebook has its own audience, and most content isn’t public. We’ve built Graph Search from the start with privacy in mind, and it respects the privacy and audience of each piece of content on Facebook. It makes finding new things much easier, but you can only see what you could already view elsewhere on Facebook.

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Now that it’s bringing on board a new CTO, however, it looks like the Carpinteria, Calif.-based company might have more to talk about.

On Monday, lynda.com announced that it had hired Frits Habermann, the former CTO and vice president of social game operations of PopCap Games (which was purchased by Electronic Arts last year) to expand its cloud infrastructure and build out its mobile and international platforms. Prior to PopCap, Habermann was an executive at Adobe, where he co-founded InDesign and was vice president of core technologies.

Since launching in 1995, lynda.com, which was founded by husband and wife team Bruce Heavin and Lynda Weinman, has built up a library of more than 1,500 video courses serving more than one million individual, corporate and academic members. On the site, users pay a subscription fee of about $25 to access the content, which aims to help anyone from novices to more advanced students learn software, business and creative skills through video tutorials produced in-house by vetted experts. The company has grown without the help of outside investment and, last year, reportedly hit $70 million in revenues.

Habermann said he comes from a family of educators and had been thinking about launching an education startup of his own when he started talking to lynda.com.

“I see a medium-sized company that is poised for growth from the point of view of things I’m interested in – the cloud, social and mobile,” he said. “My role is to help the company get to the next level.”

For starters, he said, he plans to enhance personalization and search on the site so that learners have better guidance carving out an individualized path. He also said that while the company has an iOS app, they’ll soon expand to other platforms, such as Android. Additionally, the site is minimally social in that allows members to share playlists of videos and communicates with users on Facebook, but Habermann said a focus in 2013 will be expanding into the “low-hanging fruit” in social networking.  Beyond that, he said he intends to explore live video, chat and socialization to create a more collaborative classroom – those features may take more time, but he said lynda.com “wants to be the world’s leader in that.”  To help upgrade the site’s technology, Habermann said he’ll be hiring a lean team of engineers, including those in service-oriented architecture and mobile devices.

One of the company’s advantages against its new class of competitors is its strong collection of professionally-produced content, but as other startups are showing, high-quality content is only one part of an engaging online learning experience. Updating its technology to enable more interactive and collective learning experiences will be key to helping lynda.com from falling behind.

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