A Semantic Search Approach to Task-Completion Engines

A Semantic Search Approach
to Task-Completion Engines
Darío Garigliotti

University of Stavanger, Norway

July 8th, 2018

About me
• I'm in the third year of my PhD at IAI, UiS, Norway

• My advisor is Prof. Krisztian Balog

• My work aims to understand:

• which challenges in semantic search are favorable for
supporting task-completion engines,
• which methods prove effective to model these
challenges,
• and how to integrate them into task-based search.

Semantic Search
and beyond
• More users, greater expectations:
understanding the search query

• Search engines are becoming answer engines

• Multiple techniques for query semantics

Semantic Search
and beyond
• More users, greater expectations:
understanding the search query

• Search engines are becoming answer engines

• Multiple techniques for query semantics
• "With great power comes

great responsibility"

Task completion engines
• Underlying search goal is often a complex and
knowledge-intensive task

• For example, to plan a travel

• How to get there?

• Where to stay?

• What to do?

• Task completion would provide a set of useful
properties

• To extend strategies of semantic search to help
users complete their tasks

Challenges in
Semantic Search for
Task-Completion Engines

Challenges in
Semantic Search for
Entity type
information
for
entity retrieval

Challenges in
Semantic Search for
Entity type
information
for
entity retrieval
Entity-oriented
search intents

Challenges in
Semantic Search for
Entity type
information
for
entity retrieval
Entity-oriented
search intents
Query
suggestions
to support
task-based
search

I - Identifying and utilizing
entity type information
Entity type
information
for
entity retrieval

Entity types
• A characteristic property of entities is that they
are typed

• Types are organized in hierarchies

• (or taxonomies)
…
Scientist
… ……
Person
Agent …
Enrico
Fermi

Query target types
• Target types: types of entities

sought by the query
…
ScientistArtist Writer
… ……
Person
Agent …
italian nobel prize winners

Type-aware Entity Retrieval
query entity
Olympic games
target types
Rio de Janeiro
term-based
similarity
type-based
similarity
… …
entity types
• Type information is known to improve entity retrieval

• Unlike what it seems, it is a multifaceted problem

Identifying and utilizing
• How to utilize entity type
information, with respect to
dimensions as
• the type taxonomy,
• the type representation,
• and the retrieval model?
Entity type
information
for
entity retrieval

• Type taxonomy

• Type representation

• Retrieval model

• We assume oracle-given type information

• We conduct an evaluation of dimensions in utilizing
entity type information [1]

• Type taxonomy

• Wikipedia categories


• Retrieval model



• Type taxonomy



• Most speciﬁc types

• Retrieval model


t3t3
t2t2
t5t5t4t4
t9t9t8t8
e
t6t6
t12t12
t7t7
…
t10t10 t11t11
t0t0
t1t1 …

• Type taxonomy



• Most speciﬁc types

• Retrieval model

• Interpolation

t3t3
t2t2
t5t5t4t4
t9t9t8t8
e
t6t6
t12t12
t7t7
…
t10t10 t11t11
t0t0
t1t1 …

Target Type Identiﬁcation
• "We assume oracle-given type information"

• How to automatically identify the target types for
a query, from a given type taxonomy?

• How to automatically identify the target types for
a query, from a given type taxonomy?
• We build a test collection for this task

• We develop a Learning-to-Rank approach [2]

• Our supervised learning method outperforms
existing baselines by a large margin, and does
consistently so across all query categories

Identifying and utilizing
• We evaluated multiple
dimensions of type
information

• We proposed an eﬀective
approach for type detection

• There are beneﬁts in the
type-level representations
Entity type
information
for
entity retrieval

II - Understanding and
modeling search intents
Entity-oriented
search intents

Search intents and reﬁners
• Intent: the underlying user need in a search
query

• For example, the intent of booking a hotel room
• Reﬁner: a way to express an intent in an entity-
oriented query

• For example, for booking a hotel room:
"booking", "book", "reservation", "rooms"

Entity-oriented intents
Lionel Messi

messi instagram
Lionel Messi

messi instagram

messi age
messi instagram

messi age
messi instagram
messi world cup

messi world cup

messi world cup
2006

messi world cup
2006 2010

messi world cup
2006 2010 2014

messi world cup
2006 2010 2014
2018

messi age
messi instagram
messi world cup
agemessi
instagrammessi
world cupmessi

Understanding and
• A large proportion of entity-
oriented search queries

• What do those queries ask
for, and how can they be
better fulﬁlled?
• How can we model search
intents in a structured way?
Entity-oriented
search intents

Towards an understanding
of search intents
• We deﬁne a scheme of intent categories [3]

• Website, Service, Property, Other
messi instagram => Website
lebron james net worth => Property
michigan league taxi => Service

Towards an understanding
of search intents
• We deﬁne a scheme of intent categories [3]

• Website, Service, Property, Other
Property: 28.6%
Service: 54.06%
Website: 5.34%
Other: 12.08%

A Knowledge Base of entity-
oriented search intents
1. Intents searched for a type of entities

paris map, sydney map => [city] map
2. Categories assigned to reﬁners

3. Multiple reﬁners expressing an intent

"booking", "book", "make a reservation", "rooms"


• (intent ID, searchedForType, entity type, confidence)





• (intent ID, ofCategory, intent category, conﬁdence)




• (intent ID, ofCategory, intent category, confidence)

• (intent ID, expressedBy, refiner, confidence)

Our pipeline approach
Refiners
acquisition
Refiners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...
[hotel] airport: Service

[hotel] address: Property

[hotel] expedia: Website

...
taxi

arrive

Hotel_Arrivingbooking

make a reservation
Hotel_Booking
address
Hotel_Address
KB
construction
Intent ID Predicate Object Confidence
Hotel_Booking searchedForType [hotel] c1

Hotel_Booking ofCategory Service c2

Hotel_Booking expressedBy "booking" c3

Hotel_Booking expressedBy "make a reservation" c4
Hotel_Booking expressedBy "rooms" c5

Refiners
acquisition
Refiners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...



...
taxi

arrive


make a reservation
Hotel_Booking
address
Hotel_Address
Intent

profile
{ KB
construction
Intent ID Predicate Object Confidence
Hotel_Booking searchedForType [hotel] c1

Hotel_Booking ofCategory Service c2

Hotel_Booking expressedBy "booking" c3

Hotel_Booking expressedBy "make a reservation" c4
Hotel_Booking expressedBy "rooms" c5

Knowledge base construction
- Application of the pipeline to extract all
quadruples from 581 unseen types

- 155K quadruples, 31K intent proﬁles

Excerpt of the KB, for intent ID
<aviation.airline-65-customer_service>

Understanding and
• We proposed a scheme of
intent categories

• We built a high-quality
knowledge base

• There is a large proportion of
service-oriented intents

Entity-oriented
search intents

III - Supporting
task-based search
with query suggestions
Query
suggestions
to support
task-based
search

Task-based search
low wedding budget

Task-based search
Cheap wedding cake
low wedding budget

Task-based search
Cheap wedding cake Make your own invitations
low wedding budget

Task-based search
Cheap wedding cake Make your own invitations Buy a used wedding gown
low wedding budget

Task-based search
Cheap wedding
cake
Make your own invitations
Buy a used wedding gown
low wedding budget

Task-based search
Cheap wedding
cake
Buy a used wedding gownExcerpt from TREC Tasks
test dataset
low wedding budget
1 low budget wedding dresses
0 low wedding budget cars
1 find a gown
...
0 wedding flowers
1 cup cake wedding
1 wedding cakes
...
2 wedding invitation
1 find wedding invitation templates
0 designer dresses wedding
...

Task-based search
Cheap wedding
cake
test dataset
}
low wedding budget
1 ﬁnd a gown
...
0 wedding ﬂowers
1 cup cake wedding
1 wedding cakes
...
...

Task-based search
Cheap wedding
cake
test dataset
}
}
low wedding budget
1 ﬁnd a gown
...
0 wedding ﬂowers
1 cup cake wedding
1 wedding cakes
...
...

Task-based search
Cheap wedding
cake
test dataset
}
}
}
low wedding budget
1 ﬁnd a gown
...
0 wedding ﬂowers
1 cup cake wedding
1 wedding cakes
...
...

Supporting
task-based search
• How to generate query
suggestions to support
task-based search?
• Can existing methods
generate high-quality query
suggestions?
Query
suggestions
to support
task-based
search

Query suggestions for
task-based search
choose bathroom• Given an initial query,

task-based search
choose bathroom cabinets lightning
choose bathroom decoration style
bathroom get ideas
renew ﬂoor bathroom
changing furniture bathroom
choose bathroomchoose bathroom• Given an initial query,

to get a ranked list of
query suggestions that
cover all the possible
subtasks related to the
task the user is trying to
achieve.

• Components:

• Source importance
• We propose a generative probabilistic model [4]

• We conduct a principled estimation of each of its
components
task-based search
API SUGGS. WEB SNIPPETS WEB DOCS. WH
q0

• Components:

• Document importance

components
task-based search
q0
q0

• Components:

• Keyphrase relevance

components
task-based search
q0
q0
Keyphrases

• Components:

• Keyphrase relevance
• Query suggestion

components
task-based search
q0
Query suggestions
q0
Keyphrases

task-based search
Searchliving in india
cost of living in india
american expats in india
indian classical music
india tourism
India Live TV
Searchchoose bathroom
choose bathroom brass
choose bathroom cabinets
choose bathroom colors
choose bathroom warmers
choose bathroom lighting
(a) query completion (b) query reﬁnement
• How to jointly generate query suggestions in
query completion and reﬁnement modes?
• Which are the most useful information sources?

Supporting
task-based search
Query
suggestions
to support
task-based
search
• We proposed a query
generation approach

• We studied best combinations
of sources and modes

• The diﬀerent methods
generate unique candidates

Future work
• Using target types automatically detected, and
dealing with missing type information

Future work

• Providing actionable responses, to fulﬁll the variety
of categories of entity-oriented search intents

Future work

• Providing actionable responses, to fulﬁll the variety
of categories of entity-oriented search intents

• Exploiting search intents to generate query
suggestions for supporting task-based search

I thank SIGIR for the Students Travel Grant

Thank you!
Darío Garigliotti

dario.garigliotti@uis.no

@DGarigliotti

References:

[1] Garigliotti, Darío and Balog, Krisztian. On Type-Aware Entity Retrieval. 2017. In: Procs. of ICTIR.

[2] Garigliotti, Darío and Hasibi, Faegheh and Balog, Krisztian. Target Type Identiﬁcation for Entity-
Bearing Queries. 2017. In: Procs. of SIGIR.

[3] Garigliotti, Darío and Balog, Krisztian. Towards an Understanding of Entity-Oriented Search
Intents. 2018. In: Procs. of ECIR.

[4] Garigliotti, Darío and Balog, Krisztian. Generating Query Suggestions to Support Task-Based
Search. 2017. In: Procs. of SIGIR.

Reﬁners
acquisition
[hotel] airport

[hotel] spa

[hotel] booking

...

Reﬁners
acquisition
Reﬁners
categorization
[hotel] airport

[hotel] spa

[hotel] booking

...

Reﬁners
acquisition
Reﬁners
categorization
[hotel] airport

[hotel] spa

[hotel] booking

...



...

Reﬁners
acquisition
Reﬁners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...



...

Reﬁners
acquisition
Reﬁners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...



...
booking

make a reservation
Hotel_Booking

Reﬁners
acquisition
Reﬁners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...



...
taxi

arrive


make a reservation
Hotel_Booking

Reﬁners
acquisition
Reﬁners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...



...
taxi

arrive


make a reservation
Hotel_Booking
address
Hotel_Address

Reﬁners
acquisition
Reﬁners
categorization
Intents
discovery
[hotel] airport

[hotel] spa

[hotel] booking

...



...
taxi

arrive


make a reservation
Hotel_Booking
address
Hotel_Address
KB
construction

A Semantic Search Approach to Task-Completion Engines

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