Upsana Gautam - Advanced Search Summit Napa 2019

SOUND, SEARCH,
AND SEMANTICS
UPASNA GAUTAM
Advanced Search Summit

ABOUT ME
UPASNA GAUTAM
MANAGER, SEARCH
ZIFF DAVIS
AUSTIN, TX
• Search Lead for PCMag & Mashable
• Former Clinical Research Scientist & Lab Rat
• Loud & Proud Michigander (Go Green!)
• Dance Teacher & Fitness Instructor
@upasnagautam

OBJECTIVES
• WHAT IS SEMANTIC SEARCH
• WHAT IS NOT SEMANTIC SEARCH
• HOW DOES GOOGLE MAKE IT WORK
• HOW CAN YOU MAKE IT WORK
@upasnagautam

• SEO: Then and Now
• What is Semantic Search?
• Optimizing for Voice Search
• Tactical Takeaways
AGENDA
@upasnagautam

SEO: THEN AND NOW
@upasnagautam

@upasnagautam
SEO: THEN AND NOW
Keyword-Focused
• Text retrieval system
• Relied on exact-match
• Weighted documents by keyword frequency
BACK THEN:
Unable to Distinguish Synonyms and Homographs
• Synonym: Words that share the same meaning (“car” and “automobile”)
• Homograph: Words having than one meaning depending on context (“charge”)

@upasnagautam
SEO: THEN AND NOW
• Driven by Intent and Context
NOW:
• Relevant Answers to
Specific & Vague Queries

@upasnagautam
SEO: THEN AND NOW

@upasnagautam
SEO: THEN AND NOW
“best vegan tacos austin”
“late night tex mex delivery austin”
“best happy hour margaritas 78701”
NOW:

@upasnagautam
SEO: THEN AND NOW
Search Experience Optimization
NOW:

@upasnagautam
SEO: THEN AND NOW
What enabled search engines
to understand our queries
on an intelligent level?

@upasnagautam
SEO: THEN AND NOW
The Hummingbird Update
(2013)

WHAT IS SEMANTIC SEARCH?
@upasnagautam

@upasnagautam
A branch of linguistics that studies the relationship between words and
sentences and their actual meanings.
The improvement of search accuracy by understanding intent and context,
using various on-site elements to crawl, index, and serve relevant results.
SEMANTICS
SEMANTIC SEARCH

@upasnagautam
• ENTITY OPTIMIZATION
• KNOWLEDGE GRAPH
• STRUCTURED DATA
• INFORMATION ARCHITECTURE
• CO-OCCURRENCE & CLUSTERING

@upasnagautam
ENTITY OPTIMIZATION
Paul Haahr – Google Ranking Engineer – SMX 2016

@upasnagautam
KNOWLEDGE GRAPH
•Understands relationships between
things
•Stores and understands the
intelligence between different entities
•Not just a catalog of objects, but a
data model for inter-relationships
Why don’t you explain this
to me like I’m 5?

@upasnagautam
STRUCTURED DATA
•Google is a data-driven machine that needs to be fed in order for it to learn
•Pieces of intelligence the crawler uses to build semantic relevance & authority
•This is how entities are indexed
•Speakable Schema is HERE & it’s just the beginning for voice search markup

@upasnagautam
INFORMATION ARCHITECTURE
•Allows for a crawler to clearly understand content and how it’s connected
•Provide a clear and hierarchical path of information
•Lends to a good UX
•The RIGHT approach is the most LOGICAL approach
•Must read: Information Architecture for the World Wide Web [3rd
Edition, by
Peter Morville]:
https://www.amazon.com/Information-Architecture-World-Wide-Web/dp/059652
7349

@upasnagautam
CO-OCCURRENCE & CLUSTERING
Word Co-Occurrence Clustering
•Generates topics from words frequently occurring together
Weighted Bigraph Clustering
•Uses URLs from Google search results to induce query similarity & generate topics
The combination of these two methods demonstrated greater usefulness and
accuracy when compared to Latent Semantic Analysis.
Read the patent here: https://pdfs.semanticscholar.org/dcf7/05ba07ee1b73fda0c94e9d01b2474173e470.pdf

@upasnagautam
CO-OCCURRENCE & CLUSTERING
Word Co-Occurrence
•A set of words anchors serve as initial topics, which are then generalized to other
words co-appearing with the same queries.
•Topics are created using hierarchical clustering on query similarity, which
measures to what extent two queries agree on their intersections with the list of words
in each topic.
Bigraph Clustering
•Uses organic results to create a bigraph with a set of queries and a set of URLs as
nodes. Weights of the graph are computed with the impression and click data.
•Bigraph clustering works very well even if the queries do not share common words.

@upasnagautam
LATENT SEMANTIC INDEXING
IS NOT
SEMANTIC SEARCH

@upasnagautam
BUT…

@upasnagautam
•Learning the mathematical relevance
helps to understand search on a
functional level
•LSI uses Singular Value Decomposition
which is a linear algebraic factorization
for many of our modern algorithms
•It is not a way to “do SEO”
•LSI KEYWORDS ARE NOT A THING

@upasnagautam
Latent Semantic Indexing (LSI):
•Mathematical algorithm based on Singular Value
Decomposition (SVD)
•Text indexing and retrieval method
•How terms and concepts are related
•Projects a large multi-dimensional space down into
a smaller number of dimensions
•Semantically similar words get bunched together
•Boundary blurring allows LSI to go beyond exact
keyword matching

@upasnagautam
•Noise reduction
•Reveal similarities that were latent
•Similar terms become more similar, while dissimilar things remain distinct
This method is a widely used technique to unveil latent themes in text data, as
these models learn the hidden topics by understanding document level word
co-occurrence patterns.

@upasnagautam
Short texts, such as search queries, tweets or instant messages suffer from data sparsity,
which causes problems for traditional topic modeling techniques. Unlike proper documents,
short text snippets do not provide enough word counts for models to learn how words
are related and to disambiguate multiple meanings of a single word.
*This is why the binary co-occurrence/clustering model works better*

OPTIMIZING FOR
VOICE SEARCH
@upasnagautam

@upasnagautam
OPTIMIZING FOR VOICE SEARCH
AUTOMATIC SPEECH RECOGNITION
Automatic Speech Recognition (ASR),
fueled by deep learning neural networking,
is the system that powers applications like
speech transcription and voice search.

@upasnagautam
ASR is the FORM behind the voice search FUNCTION.

@upasnagautam
How do humans do it?
Human articulation produces sound waves which the ear
conveys to the brain for processing.
New phone who dis

@upasnagautam
How Do Machines Do it?

@upasnagautam
GOOGLE’S VOICE SEARCH QUALITY METRICS
“We strive to find metrics that illuminate the end-user experience, to make sure that we
optimize the most important aspects and make effective tradeoffs. We also design metrics
which can bring to light specific issues with the underlying technology.” -GOOG
• Google has defined and uses a set of metrics
to track the quality of its voice search system.
• They use these metrics to drive their research
directions as well as provide insight and
guidance for solving specific problems and
tuning system performance.

@upasnagautam
•Word Error Rate (WER)
•Semantic Quality (Webscore)
•Perplexity (PPL)
•Out-of-Vocabulary Rate (OOV)
•Latency
Google Voice Search Case Study

@upasnagautam
The SERP has evolved into a
dynamic, purchase-driven environment,
with the integration of product carousels,
featured snippets with product rankings,
research carousels,
and of course,
the shopping carousel.

@upasnagautam
A High-Quality UX is a Fast UX
From the time it takes to detect end-of-speech to the time it takes to render
search results, time is of the essence for speech processing.
“It is generally desirable to reduce any user noticeable latency, and in
certain circumstances, may be desirable to reduce latency even if
improved speed comes at the cost of reduced quality ASR results.” -GOOG

TACTICAL TAKEAWAYS
@upasnagautam

@upasnagautam
TACTICAL TAKEAWAYS
•Craft and optimize content for topics and concepts, not just keywords
•Use structured data to feed crawler the semantic intelligence it needs to
understand your site better
--Speakable Schema is HERE and it’s just the beginning
•Align the information architecture of your website to the consumer journey
--Navigation, sitemaps, page structure, content organization

@upasnagautam
TACTICAL TAKEAWAYS
• Align the information architecture of your website to the consumer journey
--Navigation, sitemaps, page structure, content organization
• Invest in speed optimization
• Provide answers to SPECIFIC questions about your products and
services (Featured Snippets!)

@upasnagautam
TACTICAL TAKEAWAYS
Search Experience Optimization

THANK YOU!
UPASNA GAUTAM
MANAGER, SEARCH
ZIFF DAVIS
AUSTIN, TX
@upasnagautam

Upsana Gautam - Advanced Search Summit Napa 2019

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