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Query Processing and Reasoning How Useful are Natural Language Interfaces to the Semantic Web for Casual End-users? Esther Kaufmann and Abraham Bernstein.

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Presentation on theme: "Query Processing and Reasoning How Useful are Natural Language Interfaces to the Semantic Web for Casual End-users? Esther Kaufmann and Abraham Bernstein."— Presentation transcript:

1 Query Processing and Reasoning How Useful are Natural Language Interfaces to the Semantic Web for Casual End-users? Esther Kaufmann and Abraham Bernstein Presented By Stephen Lynn

2 Query Processing and Reasoning Overview  Natural Language Interfaces  Goals/Objectives  Introduce 4 Interfaces  Experiment  Evaluation Results  Future Work

3 Query Processing and Reasoning Natural Language Interfaces  Plain text queries  Phrases  Full Sentences  Challenges  Linguistic Variability (ambiguous meaning)  Domain Independence  Retrieval Performance (linked to portability)  Usefulness of NLIs

4 Query Processing and Reasoning Goals/Objectives Usability of NLIs Usefulness of NLIs

5 Query Processing and Reasoning Evaluation Interfaces  Portable  Domain-Independent  Good Performance  4 Interfaces  Least to Most Restrictive

6 Query Processing and Reasoning NLP-Reduce  Free-form text query  Remove Stop Words/Puncuation  Word Stemming  Identify Triple Structures (no details)  Enhanced Triple Store (WordNet)  Generate SPARQL  Return Results

7 Query Processing and Reasoning NLP-Reduce

8 Query Processing and Reasoning Querix  Parse Query  Extract Query Skeleton from Syntax Tree  Identifies Triple Patterns  Match Triples to Knowledge Base Resources  Generate SPARQL  Enhanced with WordNet Synonyms  Return Results

9 Query Processing and Reasoning Querix

10 Query Processing and Reasoning Querix – Ambiguity Resolution  What is the biggest state in the US?

11 Query Processing and Reasoning Ginseng  UI based on a grammar  Built dynamically from target knowledgebases  Incremental Parser  Offer possible completions (code completion)  Only accepts entries in list  No invalid queries  Convert to SPARQL  Return Results

12 Query Processing and Reasoning Ginseng

13 Query Processing and Reasoning Symantic Crystal  Graphical Display of Ontology  Select Elements in Ontology  No Invalid Queries  Specify Constraints  Incrementally Build Query  Generate SPARQL  Return Results

14 Query Processing and Reasoning Semantic Crystal

15 Query Processing and Reasoning Usability Study  How usable and useful are NLI applications?  Setup  48 subjects  4 interfaces  Same 4 questions for each interface (minor changes)  Area of Alaska?  Number of lakes in Florida?  States that have city named Springfield?  Rivers run through state that has largest city in US?  Change sequence of interfaces

16 Query Processing and Reasoning Experiment 1.Read Introduction Notes 2.Instructions on Interface #1 3.Answer 4 questions with interface 4.Fill out Usability survey about Interface 5.Repeat 2-4 for other Interfaces 6.Fill out Comparison Questionnaire

17 Query Processing and Reasoning Evaluation Results

18 Query Processing and Reasoning Evaluation Results

19 Query Processing and Reasoning Strengths  Good General Points  Automation is good (not Sematic Crystal)  Result format affects user trust  Balance between freedom and restriction  User Evaluation  Analysis

20 Query Processing and Reasoning Weaknesses  Completion time not a deciding factor in satisfaction  Still pushing Semantic Crystal  Personal Attachment  Unclear distinction between QL and Interface

21 Query Processing and Reasoning Future Work  Compare with more NLIs  Multiple Domains  Single Infrastructure w/Different Uis  Evaluate Usability/Usefulness


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