Posts filed under ‘Web 2.0’

Filtrbox vs. RSS readers/aggregators

One of the questions that I am often asked is how Filtrbox is different from traditional RSS readers and aggregators.  The following are the major differences:

Closed Search Domain vs. Open Search Domain

When using traditional RSS aggregators, the user supplies the list of RSS feeds. This means that the domain of information gathered by a traditional RSS reader/aggregator is limited to the RSS feeds that are known to the user.  I call this a closed search domain. However, in an environment such the one we have today where thousands of new content sources are being created on a daily basis and anyone can potentially become a publisher, it is unrealistic to put the burden on the user to keep up with the thousands of new content sources that are sprouting up each day.  Filtrbox takes this burdensome responsibility away from the user and discovers the new content sources for the user because Filtrbox’s search domain covers all the new content sources. I call this an open search domain. The user can also add RSS feeds to the search domain, thereby guaranteeing that their RSS feeds of interest are searched. This approach leads to the user discovering new content sources.

Publisher centric vs. Content centric

Traditional RSS readers/aggregators present to the user all the content that is published by a specific publisher regardless of whether the user is interested in the content or not. Thus, the traditional RSS readers/aggregators implement a publisher centric information consumption model. On the other hand, Filtrbox implements a content centric information consumption model.  Rather than deliver to the user all the content published by a specific publisher, whether its relevant or not, Filtrbox allows the user to filter for the content that they are interested in from ANY publisher by providing contextual keywords. The content centric model implemented by Filtrbox greatly reduces information overload because each piece of content is examined and filtered for contextual relevance before it is delivered to the user.

No filtering vs. Contextual relevance filtering

As indicated above, traditional RSS aggregators do not filter the content.  All content published by a publisher in the user’s closed search domain is delivered to the user regardless of whether it is relevant or not.  Filtrbox applies algorithms that filter content from an open search domain of publishers for contextual relevance.  Filtrbox uses multiple factors to determine the contextual relevance of content and assigns a score called FiltrRank.  The most important feature of the algorithm is that the contextual relevance algorithm learns from a Filtrbox user’s implicit interests and applies the implicit interest to future contextual relevance filtering. This means that the content delivered to the user is content that that specific user is interested in and not content other people are interested in.  Contextual relevance filtering plays a large part in the reduction of information overload.

Beyond RSS

Unlike traditional RSS readers/aggregators, Filtrbox consumes content delivery formats beyond RSS. Filtrbox is capable of consuming both standard and proprietary content delivery formats.




August 26, 2008 at 10:35 pm 1 comment

Boulder city services Radiohead-style

This is a pic of the new “Hop 2 Chautauqua” route map that I took this morning at the bus stop on Pearl and 23rd.

Radiohead-style bus fare

June 10, 2008 at 7:55 pm Leave a comment

2008 Web Search is still in 1979

On Thursday (04/24/2008 ) last week, I had the privilege of talking to Dr. Jim Martin’s Natural Language Processing (NLP) graduate class, at the University of Colorado at Boulder, about the work that we are  doing at Filtrbox and the role that current NLP students will play in the future of information technology.  This blog post is the basis of my message to the class.

As I have written before, the problem that we face today is how to harness the data that is available on the web so that we can apply meaningful interpretation to it using applications.  This problem is rooted in the assumption that the data that is stored on the web is “unstructured”.  Unlike the majority of the data processed by applications today which is stored in some form of a structure e.g. a relational database, the data on the web is not so, as its is perceived as discrete pieces of data scattered all over the web.

I told the class that part of what I am doing at Filtrbox is an attempt to prove that the data on the web is not as “unstructured” as we may think today.  Within that data, there is a lot of structure, relationship and general interconnectedness no matter how “discrete” we may think it is.  With effective mining of the data and good applications, we can apply interpretation to the data and produce meaningful information.  However, we are still far from applications that can apply effective interpretive meaning on this data.  The reason for this is that we have to address the problem of information retrieval (IR) first before we can get to the writing of applications. 

To recognize where we are today on the continuum of web data information retreival and applications; a look at the evolution of enterprise applications gives us a great analogy:

Enterprise applications are where they are today primarily because they have a structured data storage model (Relational Database or RDB) and a standard access model (Structured Query Language or SQL).  Before there were enterprise applications that we know today, there were only RDBs and SQL.  While RDB work dates back to the 1960s, the RDBs that the majority is familiar with today had their beginnings in the 1970s.  The first (or widely believed to be) commercially available implementation of RDB+SQL was Oracle, then known as Relational Software, in 1979. This provided the ability to query an RDB for data using SQL but no applications as we know them today.  Analogizing this with the web, this is where we are today. We can go on Google or our favorite RSS readers (RDB analogy) and query for web data using a weak REST API or search form (SQL analogy) but we have no applications comparative to what is in enterprise today to interpret that data.  So simply put, today we are where enterprise applications were in 1979.

My message to the class was that applications like Filtrbox are starting to barely scratch the surface with respect to the implementing of applications on top of web data.  That is because, although its 2008, we are still in 1979.  The stumbling block is the perception of the “unstructured” nature of web data. Today’s NLP students will play a large role tomorrow in identifying and establishing structure in the “unstructured” web data in order to move us beyond 1979.

April 28, 2008 at 12:51 am 1 comment

TechStars notes in the raw #2

(I took copious notes during TechStars 2007. I am opening up my notebook and sharing them with aspiring entrepreneurs.   I am going to serialize my notes on this blog.  These are my RAW notes, so sometimes people spoke too fast or were inaudible but I tried to get the gist of what they were saying. There is very little editing to these notes.)

The following questions were addressed during one of the early TechStars panels:

1) What kills most startups?

  • Surprise!! Surprise!! Not making money is not usually the big issue that causes failures unless you don’t have a vision
  • Team dynamic issues – startup failures are mostly caused by founding team friction
  • Companies fail due to execution failures. Execution failures are still team issues that can be categorized as follows: 
  1.  Team dysfunction issues
  2.  Team poor performance issues

1 and 2. are a “chicken and egg” situation

  • Do not be afraid to address team issues head on, solve them and remove the problem
  • Once you have a team issue problem that threatens your startup, re-adjust what you are doing or join another team (None of the original TechStars team members changed teams)
  • Beware of meandering, where after several weeks you are not getting anywhere. Address and re-adjust immediately because you risk team members losing passion because you are not getting anywhere

 2)  “Getting acquired” as a business model

  • Getting acquired is not a business model.  It’s a WISH!!!
  • Concentrate on building a business that has compelling value

 3) The “style” of a startup

  • You have the permission to create your own identity
  • Have an attitude
  • Have a style
  • Develop a style for your startup and yourself and work it (America’s Next Top Startup, anyone???) all the way through


March 5, 2008 at 8:52 am Leave a comment

TechStars notes in the raw #1

(I took copious notes during TechStars 2007. I am opening up my notebook and sharing them with aspiring entrepreneurs.   I am going to serialize my notes on this blog.  These are my RAW notes, so sometimes people spoke too fast or were inaudible but I tried to get the gist of what they were saying. There is very little editing to these notes.)

The following questions were addressed during one of the early TechStars panels:

 1)     Do you need a brilliant idea before starting?

  • NO!!! 
  • You just need to get going.  If you ask too many people before you start and you get feedback, you are probably selling yourself short. Just start.
  • Look for analogies in paradigms.  The first internet revolution was trying to implement an analogy of the non-digital world.  Seek the next analogy.   Also consider addressing areas that failed in the first internet revolution. 

2)     How do you know if you have an idea and you should step it up?

  • When you start having people expressing need and people catching on.
  • Listen – Listen to your peer group. Listen to the right people and the people that form your market. VCs are not necessarily the market.  
  • Sometimes you have to provide what people are going to need tomorrow (the example that was given here was what Greg Reinacker did with the concept behind Newsgator).  When you ask people, they probably will tell you what they needed yesterday and not know what they need tomorrow.  So you have to be ahead of the ball game.
  • There are two ways to describe how startup ideas evolve                                                                
  1. Scratch someone else’s itch                                                         
  2. Scratch your own itch

Ultimately you have to move from 2. to 1.  

(My interpretation of what Brad Feld was saying here is that you either have to solve problems that you are having or problems that other people are having.  But to be a successful you have to end up solving problems that other people are having if you want your idea to get off the ground)

3)     Should you start a startup in the consumer space or the B2B space?

  • Relatively indifferent to consumer or B2B. The question is how you are extracting money , long term, from the people using your product
  • At this stage, getting a great service up and running is important but most importantly you need to think of how you will make money in the long term
  • Extracting money from the customer is an engineering problem. You are thinking about the “architecture of your business”.  Address how you interact with the customer for money. The internet is free but you have to work on something monetizable
  • Some people who think that they are addressing the consumer internet now, may end up with a business solution.  Keep your mind open.


March 4, 2008 at 8:24 am 4 comments

NLP: Unstructured thinking for unstructured data

In my last blog post, I talked about how we have had to develop Natural Language Processing (NLP) algorithms in order to overcome the lack of standardization on the web.  At Filtrbox, the more we dig deeper into the web, exploring its inner depths for information, the more I find that we are having to use a NLP concept here or a half NLP concept there to facilitate the process of mining unstructured data. The application of NLP concepts is increasingly figuring into the majority of our algorithms.  I have begun to notice that my thought process as software architect, designer and developer is tending to exhibit influences of NLP and machine learning concepts much more than before. 

I think NLP fundamentals are essential for those who wish to undertake the challenge of building the next generation of web applications that process the unstructured data on the web.  Yes, there are efforts to build a structured web via initiatives such as the semantic web and the various APIs being proposed. I respect these efforts; however, I would not solely rely on these initiatives alone.  The proposed APIs provide access to structured data stored on various islands on the web.  For those users who do not have their data on those islands, their data is not accessible via the API.  The Semantic Web is the initiative that will bring us closest to structured data on the web.  However, as we are witnessing its painfully slow adoption, it looks like its going to be a while before we have some structure on the web. The challenge is what do we do now while we wait for these initiatives to mature. I think what we do today is, instead of waiting for content publishers to structure their content, we process content publishers’ content as is and we programmatically infer the structure of the content.  The application of NLP concepts are one way we can make the content structure inferences.  By applying NLP, this will take us a step closer to programmatic input, processing and storage of unstructured data.  We have traditionally thought in terms of structured data, programmed for structured data and stored structured data.  The challenge posed by the web today is an opportunity to break new ground for software engineers and start thinking, programming and storing unstructured data.

February 29, 2008 at 8:56 am 2 comments

A case for standardizing blog templates

Alex Isikold of AdaptiveBlue has published a great post on “How YOU can make the web more structured”.  A section of this post, “Standardizing Blog Templates Across Platforms”, really resonates with me.  Isikold is suggesting that blogging platforms such as WordPress and TypePad standardize their templates.  Why is this important? 

To help answer this question, here is the Web 2.0 school of thought that I subscribe to:  Let’s start off with an enterprise database analogy. The basic assumption is that blogs are nothing but a data store.  While information in a blog makes for an interesting read, it is about as interesting as reading data in a text column in a relational database.  While the data in a single text column may have a lot of meaning, its meaning and usefulnes is enhanced when the data is combined with other columns in the same table in database, or with other tables in the same database, or even with data in other databases. The wealth of data is hidden in its interconnections with other data. In order to harvest the wealth of data in databases, applications are built on top of the databases that reference and make relational semantic inferences between the data in the database(s).  Today, blogs are the database(s). What is lacking are the applications that harvest the wealth of information stored in the blogs.  These are the applications that the next wave of Web 2.0 companies (including myself) are working on. 

The pace of these next generation applications is being hindered by the lack of a consistent structure (standard) in blog data. What Isikold is bringing attention to is that unlike relational databases, which adhere to relational database management system standard (characterized by a simple TABLE/COLUMN/ROW+SQL structure that has been consistent over the years), blogs have no such standard. The structure of blogs is currently left up to the blogging platforms such a WordPress, Typepad etc. Blogging standards today are akin to having Oracle, SQL Server, MySQL each using a different standard for storing and retrieving information. Not only a different a standard for each of the databases, but a different standard for each version of each database.  Exacerbating the problem further, each of the different databases being customizable by anyone and anyone can change the standard to a standard of their liking. If these databases were is such a state, it would be very difficult to write any applications that leverage data from these databases. ODBC and JDBC standards would be very unreliable, if not useless.  Such is the state of the blogosphere today when one looks at it from a data interface perspective.  

As many of you know, I am currently devoted to work on the layer of applications that leverages the data in blogs and beyond in order make such data more useful to users.  The lack of standardization (as described above) makes it difficult to identify the content in blogs.  Content identification is important because an application needs to be able to identify the difference between actual blog post text and some other text on the blog so that analyses and inferences can be established appropriately.  I have been monitoring the different types of templates in an attempt to predict template patterns for the different blogging platforms (mainly WordPress, TypePad, Blogger, MovableType).  I came to the conclusion that pattern prediction is only successful to a certain point due to the following

1) the original templates from the blogging platform vendor consists of multiple major and minor versions that do not have a predictable consistency in the template content tagging and

2) there are modified/hand coded templates floating out there which are totally unreliable.

As a result of these observations, I have resorted to writing my own content identification algorithms that include a combination of template pattern predictor algorithms and NLP based semantic blog post text identification algorithms.  While this has served me well up to now, a blog template standard will be very beneficial not only to myself but many people who have not figured out how get past the problem.  

Isikold is suggesting that a standard be adopted with the goal of giving blog templates a consistent structure.  This means the adoption of a template standard that identifies the different types of data on the different parts of bogs post. Isikold is suggesting that on a blog post, the template should make it easy to identify the blog post text, the side bar, the name of the author, the data that blog post was published, the tags for the blog post content and the blog posts comments.  I believe an adoption of this simple template will go a long way in helping to bring the next wave of Web 2.0 applications to market faster.  I support a blog template standard.

February 4, 2008 at 9:06 pm Leave a comment

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