How to Improve Your Google Ranking: Myths and Reality Ao-Jan Su

†

Y. Charlie Hu

‡

Aleksandar Kuzmanovic

†

Cheng-Kok Koh

‡ †

Northwestern University

‡

Purdue University

Motivation

● Internet search engines (e.g. Google) drive users to highly ranked pages ● Search engines ranking results greatly influence how people acquire knowledge from the Internet [Pan ‘07] ● It is desirable to understand how a search engine ranks web pages ● Search engines’ ranking algorithms are proprietary ■ Publicly available information is very limited and out dated

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Current Approaches

● Guess-works by webmasters ■ ■ Trial and error Inefficient ● Based on experience of search engine optimization (SEO) experts

Ao-Jan Su

Lack of systematical studies leads to folklores

How to Improve Your Google Ranking: Myths and Reality

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Various Ranking Feature Opinions

SEO experts Survey of marketing expert Internet users

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Goals & Challenges

● Goals ■ ■ Systematically approximate a search engine’s ranking results Identify the importance of ranking factors ● Reverse-engineering a search engines’ ranking algorithms can be very complicated ■ ■ Numerous ranking factors

−

Google claims to have over 200 ranking factors Sophisticated ranking functions

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Our Approach

● Build our own ranking system to approximate search engines’ ranking results • •

Learning models:

Linear programming SVM

Recursive partitioning

•

algorithm:

Capture non-equational behavior of ranking functions.

Ao-Jan Su New ranking system:

Generate our own ranking results and compare to Google’s

How to Improve Your Google Ranking: Myths and Reality

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System Architecture

● Components of our ranking system ■ ■ Crawler Ranking Engine Can we approximate Google’s ranking results (top 10 pages) by using our own ranking system?

How to Improve Your Google Ranking: Myths and Reality

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Ao-Jan Su

Ranking Features

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Learning Models

● ● Linear programming model ■ ■ Minimize the distance between our ranking system and Google’s Minimize objective function Ranking difference between the 2 pages Out of order => penalty  (

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 1

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

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(

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) Weight: highly ranked pages ■ ■ General technique for learning to rank programs Support linear and polynomial kernels 9

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

Recursive Partitioning Algorithm

● Multiple layers of indices ● Non-equational ranking algorithm Train or apply ranking models and continue the recursion The algorithm ends when we found top X pages

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Experimental Evaluation

● Evaluate different ranking models ■ Which model has better prediction accuracy?

● Evaluate the effectiveness of recursive partitioning algorithm ■ Can recursive partitioning algorithm improve prediction accuracy?

● Evaluate the relative weights of ranking features ■ Which ranking feature is more important?

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Experimental Setup

● Crawl top 100 pages of 60 random keywords ● Randomly select 15 keywords as the training set with the rest 45 keywords as the testing set ● Evaluate the accuracy of our ranking system by predicting Google’s top 10 pages for each keyword in the testing set

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Comparisons of Ranking Models

The performance of our customized linear learning is better than SVM-linear model The performance of the polynomial model is better than both linear models.

At the cost of:

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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The Power of Recursive Partitioning

The recursive partitioning algorithm does help to improve accuracy of the ranking system in every round 3 rounds of recursive partitioning successfully “smooth out” the non-linearity of Google ranking algorithm and achieve a high prediction accuracy

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Weights in Different Rounds in a Linear Model

Page rank score, keyword in title and hostname are the top 3 ranking feature Keyword in meta-description tag matters but in meta keyword tag does not In different rounds, the learning model produces different set of weights

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Case Studies

● Can we improve our ranking system’s accuracy by isolating a subset of ranking features ■ Example: remove the age factor by focusing on “young” pages ● Can we use our ranking system to detect biases in search engines’ ranking algorithms?

■ Example: blogs ● Can we validate or disapprove new ranking features?

■ Example: HTML syntax errors

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Isolating Subsets of Ranking Features

We crawl web pages less or equal to 24 hours old to

remove

ranking features of specific, our ranking system performs better improves to 80% for 92% of evaluated keywords

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Negative Bias Toward Blogs

We categorized web pages to different categories (e.g. blogs,

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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HTML Syntax Errors do not Matter

We add a new ranking feature (hypothesis) for the ranking feature does not make an impact

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Conclusions

● In this work, we show that it is possible to systematically approximate Google’s ranking results with high accuracy ■ By a linear learning model incorporated with a recursive partitioning scheme ● We reveal the relative importance of ranking features in Google’s ranking function ● We illustrate our system can validate or disapprove ranking features and detect ranking bias

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

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Thank you!

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Backup Slides

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Linear Programming Model

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality

Query Keywords

Ao-Jan Su How to Improve Your Google Ranking: Myths and Reality