They haven’t been Techcrunched or boingboing’ed as yet so the number of sites in the system is low, which limits the utility of the service. However, a search for ‘Search Engines’ has been pre-populated. It would be useful if there were a way to seed the system with results from another service. I also think real money would be an interesting addition. As it is, only the ongoing addition and betting on sites by sufficient users will reveal whether the model actually works. But I have to say.. it looks good on paper. Would I invest real money in Tall Street? No. But then I’m not an investor on the lookout for innovative new ideas.

Yes, it’s just another student project, and it looks a bit rough. But haven’t we seen something fitting that description before…?

Gary was also good enough to answer a few questions for me:

Could you explain briefly how tall street works.

Traders make investments on sites belonging under keywords. They get rewarded (their investments increase) if when people who search those keywords find their sites useful (based on if the link gets clicked and any ratings the link gets) and punished if not.

Can prediction markets work for search when there are so many ‘correct answers’?

This is a problem any search engine struggles with.

The ideal situation is:
The user has some idea about what they want, they express this in “search terms”, the search engine returns the best answer for what the user wanted.

A search engine works by:
Returning all the pages that contain that term (or had that term in the anchor text to that page). Then it ranks those pages based on some algorithm which takes into account the number of pages linking to it, (and linking to those pages) among other things.

Tall Street works by:
Returning all the pages that someone thought belonged under that search term, and the rankings are influenced by

1) how many people thought that site belonged under the term (if lots of people invest in a site it gets lots of investment then it gets a high ranking),

2) how much they thought the site should be ranked in comparison to other sites under that term (some unpopular terms might only have one investor in, and they could completely control the rankings for that search term, this is fine since if someone disagrees then they are able to invest more heavily and change the rankings),

3) how much influence (money) the investors investing in the sites under the term have over the directory i.e. their net worth (if that investor is good investing in popular sites then over time they will get more influence since they will accumulate more money)

Why is this better?

Rankings are up-to-date — the link structure of the web that search engines analyse to determine rankings isn’t dynamic — links remain long after a site moves. What could happen with Tall Street is if some site added a new cool feature that no other site under the keyword had, then investment in that site could increase and it’d end up at the top of the results straight away. You wouldn’t see something like this in the link structure until long after. ( i.e. The feature would have to be very cool that people decided to link to the site and then the search engine would have to recrawl the web, and then update the results)

Users can find sites by type and easily find similar sites — Sites are under keywords because people thought that the site belonged under the key words. With search engines you get lots of results many aren’t relevant. They just appear because they contain the term you are searching for on the page. We have a feature where you can drill down to find pages under keyword1 and keyword2, which lets you easily find similar sites e.g. http://www.tallstreet.com/view/PHP/tutorial/
Fair Ranking system — Everyone gets an input into the rankings. If you think a site doesn’t belong, you can mark it as spam. If you find a site that is better then what is showing as the best then you can sign up and invest in it. If you’re right and other people agree, then you’ll make more money and have more influence over the directory.

At a later stage, we could allow traders to group together and publish their portfolio. This means you could search for ‘what do New Zealanders think is the best news site’. Or ‘what do web developers think is the best reference site’. This isn’t something a search engine can do as easily.

Is this a web 2.0 product, and how so?

My aim in the project is to create a cool fun website that I think it’ll help make finding good sites easier. I guess if you follow the definitions on

http://twopointouch.com/2006/08/17/10-definitions-of-web-20-and-their-shortcomings/

It has to some degree:
The wisdom of crowds
Shared Web Applications
User Participation

But mainly because I think these elements will help produce the best result.

I try to allow the site to work even if you don’t have javascript (we do not rely on AJAX) and provide an AJAX way if I think it can help usability.

I would argue that you should narrow down a little on what you search for, to gain a little traction in a few limited ‘best of’s. What’s your answer?

My view is to provide some value to people as early as possible. You are right. Limiting would show exactly how the product works. But one way we give users value is to allow them to add their own site under keywords. This is fine since if they if they are spamming they will be punished, and if they want to earn lots of money to invest in their site they will need to play the game well and make good investments in other sites. We could publish some of the popular search terms on the front page, or if people want to recommend some categories to promote we could do that.

Who are you and where are you from (professionally and geographically)?

I’m a software engineering student from the bottom of the world (New Zealand). I have been working for an ecommerce store which is where I picked up the skills to do this.

How are you funded currently?

Currently the project is experimental rather then an actual company, it’s self funded.

What are your plans for this going forward?

The real problem is gaining users, the site isn’t useful unless people use it, and people won’t use it unless its useful. This is made harder by the fact we have $0 marketing budget.

The key things we are concentrating on at the moment are:
– We are trying to add in content to make the site more useful.
– Getting users.

Frankly, even though I’m supposed to be an investor, the ideas that excite me most are not necessarily the ones that make the most money, but the ones that blow away evil old monopolies. For example, I love collaborative news sites not so much because they make a lot of money — though they might — but because they’ve shown what a bad job the ‘old media’ were doing.

Most people don’t understand what a social force startups can be. There are a lot of changes that can only happen through companies. One startup I dream of funding is the one that kills the record companies. You know your business model is broken when you’re suing your customers. The new business model must be out there somewhere, and my guess is that the way to beat the bad guys is not through political action (or at least, not only that), but by inventing
whatever replaces them.

(Parochial headline alert: PG Tips is a brand of English tea.)

It turns out that that is one of the more difficult questions. (Damn!) It depends on what you mean. You might mean turning the billions of existing web sites semantic or only about possible future sites or services. The second of these options is the most likely outcome at the present. Semantic web is partly about annotating web pages to make them amenable to machines. John prefers the expression ‘semantic technologies’ to avoid this confusion.

At the moment, information on the web is pretty much designed for human consumption. You and I know when we go to a shopping site that the figure in bold is the price, that a certain number is the product code and that this piece of information is about the shipping information. To a machine, it may make no sense whatsoever. If machines are to be able to bring together all these different pages to make the web more useful, then they need to be able to read them.

We’ll see the first applications of semantic technologies in the enterprise space. Its need is more acute. They have lots of databases, all built by different people according to different rules. Integrating the information from those is already a very costly and time-consuming activity. One database may talk about CustomerName, another may refer to CustomerID, for example. Joining these things together, so perhaps, a support department knows about what equipment the logistics department has installed for a customer, improves business efficiency. Semantic technologies put what Davies called a “wrapper” around these different data sources to create overarching access, connecting different datasources in a way that doesn’t require nearly so much human effort.

People developing semantic technologies work by developing an ontology for understanding the sort of data it’s looking at and the technology will be able to do some reasoning based on this. An ontology means a form of classification system for whatever it is that’s being examined. For foods, that might include their ingredients, nutritional properties, suppliers and type. It’s not just a list, though, but will also understand the relationships between different items. An ontology developed for food might come across E101 and additives and CrispyPop bar. It will know that E101 falls under additives which are part of the ingredients of the bar. If that description then gets combined with a database of shops at a wholesaler where you might send the bar, then the semantic agent will calculate that health food shops aren’t going to stock CrispyPop bars. It’s not intelligence in any way, but the application of rules that the creators have decided upon.

Because the semantic technologies are lightweight and open source, they are potentially available to any company. For this reason, enterprises that get some of their data from external sources will still be able to use semantic approaches to integrate and drill the ensuing combination. These are my words, not John’s, but one way to think of the technologies is as providing a toolkit for more easily creating web mashups. Companies already exist, such as Cerebra and Ontoprise, to sell ways to integrate enterprise information using OWL, the web ontology language.

I kind of understood, so far, but I needed a good example. I suspect you may be the same.

BT works closely with the National Health Service in the UK. The Service has already gone a long way into digitising and collating its information through the Electronic Patient Record system and also information on medical knowledge through the SNOMED classification system. Unfortunately, though, the data can still be very dispersed. The X-Ray department might have a patient’s data on a different system to the Pharmacy, for example, and those might be completely unconnected to the systems used in a different hospital or by a clinic.

What semantic web technologies bring to this is unity and also what John called Description Logics. It can prise open the different databases, allow an overview, but also calculate with it. Imagine a patient’s medical record says that they are allergic to almonds. Then a doctor misses this and somehow prescribes a nut-based food. When the nurse enters this into the patient’s record, the semantic application will use its ontology to work out that almonds are nuts and that therefore this is a very bad idea. Semantic technologies that can perform calculations like this, and potentially save lives, are already in use in the UK Health Service.

I’ll leave this there for today. My head hurts already. If there’s interest, I’ll be happy to do a follow-up on another day.

It’s fairly predictable of me, but I don’t think it’s fine at all. Here are four reasons why it’s bad:

(a) This is likely to lead to weaker published interviews. A one-hour interview can potentially contain over 20,000 words. Which interviewee is going to take the trouble to write that down? What a conscientous journalist does is take those 20,000 words and produces 3000 words that are cogent, interesting and helpful to the reader.

(b) It leads to delays, sometimes considerable, between asking the question and getting the answer. This might mean that the interview is no longer newsworthy and a waste of everyone’s time. For a major news issue, that means important questions can remain unanswered. For a professional writer, that’s also their livelihood.

© It leads to over-polished and cloned responses. These aren’t interesting to publish or read. What’s interesting is when people are challenged, actively thinking, perhaps even a little emotional. It’s hard to deduce a person’s personality from their carefully crafted, balanced email responses. It can even lead to responses that have really been written by the interviewee’s PR company. I am sure this has happened to me on occasion. If what the new media advocates are asking for is transparent representation, how is this helping?

(d) There’s an assumption here about power. The assumption is that the reporter holds power over the poor A-list blogger. Not quite sure where that comes from, to start with. Written responses, it is argued, are helping to put the power back in the hands of the interviewee. This alleged balance of power is not often the case with interviews.

Most interviews are with very powerful people whom the media ought to be putting on the spot. That’s why they are being interviewed. If somehow I interview the CEO of a major corporation that has just poisoned a village due to faulty safety procedures, do you really want him/her to be able to say, “I’ll answer your questions on my blog”? This is not journalism’s function in society. It’s supposed to question and challenge and expose untruths.