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Search Marketing Round Up

Written by David Harry   
Wednesday, 04 June 2008 09:24


Some links of interest for the last week from my FriendFeed Rooms and the land of patents. If you know of some other great posts I have missed, be sure to join our rooms and post to yer heart's content and it might just show up here next week!

Search Engine Marketing – from the SEM Room

Get free links on Search Engine Watch – SEOmoz
8 Arguments Against Sculpting PageRank™ with Nofollow – Audette Media
Improved Google SEO Documentation – Matt Cutts
Time Warner Cable tests metered Internet service – Reuters
Yahoo!, Google, Microsoft Clarify robots.txt Support – Search Engine Land
More from microsoft on Page Segmentation – SEO by the Sea
Google SERP-rot, Paid Links, & Spam Classification – Aaron Wall
The Top 100 Alternative Search Engines June – Alt Search Engines
SEM Boot Camp - Alphabet Soup and PPC – eMarketing Performance
SEO Defence: Why Defending Your Position is Necessary! – SEO Design Solutions
Optimizing Universal Search Results for Local Businesses – Fuel Interactive
Link Lust; a lesson in .edu link building - SnydeySense


Learn SEO – goodies from the Learn SEO Room

Blow Your Mind Link Building Techniques – Search Engine RoundTable (SMX Coverage)
How to explore backlink anchor text – Search Engine Journal
Site Network Stealth and Uses: Hiding from Google and Competitors – SlightlyShady
Developing a SEO Strategy - Part I – SearchRank
THE TEN COMMANDMENTS OF SEM 2.0 – Fuel Interactive
The simplest ROI of blogging in SEO: Link building – SEO Optimize
Link Worth – What’s yours worth – Tim Nash
Don't sour your link juice by forgetting Basic SEO – Andy Beard
Study Finds Searchers' Patience Lessening – WebPro News



 Patent Bending – Below are some patents of interest that came out over the last week; 

Google Patents –

Method and apparatus for characterizing documents based on clusters of related words -
Abstract – “One embodiment of the present invention provides a system characterizes a document with respect to clusters of conceptually related words. Upon receiving a document containing a set of words, the system selects "candidate clusters" of conceptually related words that are related to the set of words. These candidate clusters are selected using a model that explains how sets of words are generated from clusters of conceptually related words. Next, the system constructs a set of components to characterize the document, wherein the set of components includes components for candidate clusters. Each component in the set of components indicates a degree to which a corresponding candidate cluster is related to the set of words.

Yahoo Patents –

Systems and Methods Using Query Patterns to Disambiguate Query Intent -
Abstract - Apparatuses, methods, and systems directed to disambiguating queries. Particular embodiments can be used in connection with query analysis and query rewrite processes to determine the intent of one or more keywords contained in a query.

MSN Patents–

Method and system for identifying object information (more page segmentation stuff) -
Abstract - A method and system for identifying object information of an information page is provided. An information extraction system identifies the object blocks of an information page. The extraction system classifies the object blocks into object types. Each object type has associated attributes that define a schema for the information of the object type. The extraction system identifies object elements within an object block that may represent an attribute value for the object. (also covered in depth by Bill)

 Ranking database query results using probabilistic models from information retrieval -
Abstract - A system and methods rank results of database queries. An automated approach for ranking database query results is disclosed that leverages data and workload statistics and associations. Ranking functions are based upon the principles of probabilistic models from Information Retrieval that are adapted for structured data. The ranking functions are encoded into an intermediate knowledge representation layer.


... and there we have it... more next week - L8TR

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