Date: February 27, 2018 Venue: Stavanger, Norway. UiS TN910 - Innovation and Project Awareness Please cite, link to or credit this presentation when using it or part of it in your work.

1. A Semantic Search Approach
to Task-Completion Engines
Darío Garigliotti
TN910 - Innovation and project awareness
UiS - February 27, 2018

2. Background: Semantics
- An entity is an individual or thing, uniquely identified
Henrik Ibsen, Stavanger, UEFA Champions League
- We describe entity properties using triples
- Attributes: (Henrik Ibsen, birthdate, 20 March 1828)
- Types: (Henrik Ibsen, is a, writer)
- Relations: (Henrik Ibsen, work, A Doll’s House)
- A knowledge base (KB) is a set of triples.
- For us, semantics == structured knowledge
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3. Semantic Search
- "With great power comes
great responsibility"
- More users, greater expectations:
understanding the search query
- Search engines are becoming answer engines
- Multiple techniques for query semantics
- I am focusing on the next evolution stage:
task completion
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4. Objective
- My research goal is to understand:
- which challenges in semantic search are promissory
for supporting task-completion engines,
- which methods prove effective to model those
challenges,
- and how to integrate them into task-based search.
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5. Techniques: Semantics in
Current Search Engines (1)
Type
Other
properties
Entities and
documents
Entity
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6. Semantics in Current
Search Engines (2)
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7. Status
- I'm in my third year of studies in Computer
Science
- I have made contributions in these challenges:
- utilizing entity type information for entity retrieval
- understanding entity-oriented search intents
- generating query suggestions to support task-based
search
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8. Stakeholders and Societal
Factors
- Social groups of relevance: Research
1. Colleagues in my research group
Collaboration, integration
2. Researchers in the same area
Contribution; competition
3. Researchers in related areas of the field
Usefulness e.g. for evaluation; competition for areas
4. Researchers in related fields
Usefulness of our/their developments 8

9. Stakeholders and Societal
Factors
- Social group of relevance: Industry
1. Commercial search engines
Possible utilization of our developments
2. Major web-based services
Possible utilization of our developments, benefit form
our possible system demos reaching them
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10. Stakeholders and Societal
Factors
- Social group of relevance: Developers
- Benefit from our released codebase(s)
- Social group of relevance: Users
- Indirectly, when major engines or services implement
our developments
- Directly, only in minor scale through system demos
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11. Stakeholders and Societal
Factors
- Interpretative flexibility
- For users: a solution for completing tasks
- For major commercial engines and services: to increase
the quality and diversity of offers, then, their usage, and
revenues
- For other services: their promotion in responses
- For researchers: contributions, and curiosity
- Closure is hard to foresee
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12. Challenges in RRI
- Scalability
- Whether our models and results are indeed extensible
as working solutions on larger, real data
- Data Privacy
- Anonymization of datasets (collected by us or
provided by previous work)
- Development of tasks and evaluation methodologies
oriented to protect privacy
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13. RRI Measures
- RRI goals
- "respond to needs and ambitions of society, reflects
its values, be responsible..."
- "societal actors work together during the whole
research process..."
- privacy, security among the values by which to
evaluate research outcomes and options
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14. RRI Measures
- EPSRC AREA framework
- Reflect:
‣ the closer to a practical implementation of a working
solution, the larger the reflections should be on
motivations and implications: dilemmas, social
transformations
‣ permanent reflection on assumptions, questions,
areas of ignorance
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