Difference between revisions of "Knowledge-Aware-Search"

From Knoesis wiki
Jump to: navigation, search
(People)
(People)
Line 9: Line 9:
 
[http://knoesis.wright.edu/researchers/delroy/ Delroy Cameron] <br />
 
[http://knoesis.wright.edu/researchers/delroy/ Delroy Cameron] <br />
 
[http://knoesis.wright.edu/amit Amit P. Sheth] <br />
 
[http://knoesis.wright.edu/amit Amit P. Sheth] <br />
Nishita Jaykumar <br />
+
[http://knoesis.org/researchers/Nishita/ Nishita Jaykumar] <br />
 
[http://knoesis.org/researchers/gaurish/ Gaurish Anand] <br />
 
[http://knoesis.org/researchers/gaurish/ Gaurish Anand] <br />
 
[http://knoesis.wright.edu/tkprasad/ Krishnaprasad Thirunarayan] <br />
 
[http://knoesis.wright.edu/tkprasad/ Krishnaprasad Thirunarayan] <br />

Revision as of 03:04, 11 March 2014

This wiki contains supplementary materials for the research article currently under review. This research is part of the PREDOSE project, which is an inter-disciplinary project between the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) and the Center for Interventions, Treatment and Addictions Research (CITAR) at Wright State University. PREDOSE is the acronym for PREscription Drug abuse Online Surveillance and Epidemiology.


Overview

While semantic search has become a viable alternative to classical keyword-based search, a review of existing semantic search techniques and semantic search engines (Hakia, DuckDuckGo) reveal a considerable misalignment between the mental model of a user's information need and the knowledge model developed to meet such needs. There is an assumption that assertions in ontologies provide sufficient coverage to appropriately interpret the user information need. Hence minimal (often inadequate) support is provided for interpreting additional elements (such as those that convey intensity, frequency, time intervals, etc), not necessarily modeled in ontologies. In reality, many complex search scenarios require a knowledge of such constructs and extend beyond the boundaries of ontologies altogether. In this work, we develop a context-free grammar that defines the query language interpretable by the our knowledge-aware system. In an evaluation against the popular search engine Google, a popular semantic search engine Hakia and a crowd-sourcing based search engine DuckDuckGo, our Knowledge-Aware Search system outperformed the state of the art in retrieving relevant documents for two complex information needs.

People

Delroy Cameron
Amit P. Sheth
Nishita Jaykumar
Gaurish Anand
Krishnaprasad Thirunarayan
Gary A. Smith

Framework

Our Knowledge-Aware Search Framework consists of three components: 1) a module for Query Interpretation; 2) text analytics for Document Annotation and 3) a Query Matcher.

Query Interpretation

Our module for query interpretation consists of: 1) a Knowledge Model and 2) The Context-Free Grammar

Knowledge Model

The Knowledge Model is the Drug Abuse Ontology (DAO - pronounced dow), which is the first ontology for prescription drug abuse ever created. An OWL version of the DAO is available online for browsing. In our Knowledge-Aware Search system, we interpret keywords according to the lexical/syntactic match between keywords and concept labels in the ontology. We then expand the query with labels and slang terms for the matching concepts (whether a Class or an Individual) and all labels and slangs terms from Subclasses of the given concepts in the ontology hierarchy.

NB: There is no novelty in our approach for ontology-based query interpretation, and we make no claims to that effect in this aspect of our work. Our novelty comes from demonstrating the limitations of ontology-based query interpretation for complex information needs, which often require background knowledge outside of the ontology. To illustrate this, we develop a context-free grammar to define the query language interpretable by the system, which includes information from: 1) the ontology; 2) lexicons; 3) lexicons combined with the ontology (lexico-ontology) and 4) the alphabet of the grammar. In the next section we present details on the grammar.

Context-Free Grammar and Query Language Specification

LEGEND

ALPHABET
ONTOLOGY
LEXICON
LEXICO-ONTOLOGY
EXAMPLES


Ubiquitous Nonterminals

EQUIVALENCE
> greater than | more than | above | in excess of | slightly above | little more | bit more | slightly more | high | higher | highest | higher than
< less than | lower than | below | in lack of | slightly below | little less | bit less | slightly less
= exactly | precisely
>= greater than or equal to | more than | above | in excess of | slightly above | little more | bit more | slightly more | exactly | precisely | high | higher | highest | higher than
<= less than or equal to | less than | lower than | below | in lack of | slightly below | little less | bit less | slightly less | exactly | precisely

 

DEFINITIONS
NUMERIC_AMOUNT -999.99 | ... | 0 | ... | 3-4 | ... | 24/7 | 999
WORDED_AMOUNT one | once | two | twice | three | thrice | four | five | six | seven | eight | nine | ten | eleven | twelve | thirteen | fourteen | fifteen | sixteen | seventeen | eighteen | nineteen | twenty | thirty | forty | fifty | sixty | seventy | eighty | ninty | hundred
NUMBER 0 | 1 | ... | 100
AMOUNT NUMBER |
WORDED_AMOUNT
RANGE [0 - NUMBER] WORDS

 

NS Nonterminals

Class Name Class Source Class Type
INTERVAL Alphabet Compound
FREQUENCY Alphabet Compound
DOSAGE Alphabet Compound
ENTITY Ontology Simple
ROA (Route-Of-Administration) Lexicon/Ontology Simple
DRUGFORM Lexicon/Ontology Simple
SIDEEFFECT Lexicon/Ontology Simple
EMOTION Lexicon Simple
PRONOUN Lexicon Simple
INTENSITY Lexicon Simple
SENTIMENT Lexicon Simple

 

Ontology Nonterminals
Buprenorphine addnok | bup | bupe | bupes | bupey | buprel | buprenex | buprenorphine | buprenorphine analgesic | buprenorphine opioid dependence | buprenorphone | buprigesic | bups | butrans | film | films | morgesic | norspan | probuphine | saboxine | sobos | strip | strips | sub | subbies | subox | suboxene | suboxone | suboxone film | suboxone tablet | subs | subutex | tecs | temgesic | tex | tidigesic | xone
Heroin

 

Alphabet Nonterminals
INTERVAL
PAST_DETERMINER ago | prior | previous | since | before | last | past
PRESENT_DETERMINER now | about | around | several | couple | every | all | this
FUTURE_DETERMINER next | later | after
PERIOD PAST_DETERMINER |
PRESENT_DETERMINER |
FUTURE_DETERMINER
TIME_INDICATOR
HOUR hour | hours | hr | hrs
MINUTE minute | minutes | min | mins
SECOND second | seconds | sec | secs
DURATION_INDICATOR
DECADE decade | decades
YEAR year | years | yr | yrs | annum
MONTH month | months | mth| mths | mo
WEEK week | weeks| wk | wks
DAY day | days | night | nights | nite | nites | morning | mornings | mornin | evening | evenin | evenings | afternoon | noon
DURATION_PERIOD PAST_DETERMINER RANGE PERIOD years ago, weeks prior
PRESENT_DETERMINER RANGE PERIOD weeks now
FUTURE_DETERMINER RANGE PERIOD weeks later, days after
PERIOD_DURATION PAST_DETERMINER RANGE DURATION_INDICATOR last year, previous day
PRESENT_DETERMINER RANGE DURATION_INDICATOR about a year, around a month
FUTURE_DETERMINER RANGE DURATION_INDICATOR later years, next day
TIME_PERIOD TIME_INDICATOR RANGE PAST_DETERMINER hours ago, minutes before
TIME_INDICATOR RANGE PRESENT_DETERMINER hours now
TIME_INDICATOR RANGE FUTURE_DETERMINER hours later, minutes after
PERIOD_TIME PAST_DETERMINER RANGE TIME_INDICATOR last hour
PRESENT_DETERMINER RANGE TIME_INDICATOR several hours, couple of minutes
FUTURE_DETERMINER RANGE TIME_INDICATOR next hour
AMOUNT_TIME_PERIOD AMOUNT RANGE TIME_PAST_PERIOD 5 minutes ago
AMOUNT RANGE TIME_PRESENT_PERIOD 10 hours now
AMOUNT RANGE TIME_FUTURE_PERIOD 5 minutes later
AMOUNT_TIME AMOUNT RANGE TIME_INDICATOR 15 seconds
PERIOD_AMOUNT_TIME PAST_DETERMINER RANGE AMOUNT_TIME last 2 hours, past 2 minutes
PRESENT_DETERMINER RANGE AMOUNT_TIME around 2 hours
FUTURE_DETERMINER RANGE AMOUNT_TIME next 15 seconds, after 2 minutes
AMOUNT_DURATION_PERIOD AMOUNT RANGE DURATION_PAST_PERIOD 5 years ago
AMOUNT RANGE DURATION_PRESENT_PERIOD 5 years now
AMOUNT RANGE DURATION_FUTURE_PERIOD 5 years later, 9 months after
AMOUNT_DURATION AMOUNT RANGE DURATION_INDICATOR 15 months
PERIOD_AMOUNT_DURATION PAST_DETERMINER RANGE AMOUNT_DURATION last 15 weeks, last 2 years
PRESENT_DETERMINER RANGE AMOUNT_DURATION about 3 monts, around five years
FUTURE_DETERMINER RANGE AMOUNT_DURATION next 15 weeks, after 2 years
INTERVAL DURATION_PERIOD |
PERIOD_DURATION |
TIME_PERIOD |
PERIOD_TIME |
AMOUNT_TIME_PERIOD |
AMOUNT_TIME |
PERIOD_AMOUNT_TIME |
AMOUNT_DURATION_PERIOD |
AMOUNT_DURATION |
PERIOD_AMOUNT_DURATION

 

FREQUENCY
FREQUENCY_ITEM hourly | daily | weekly | bi-weekly | biweekly | monthly | yearly | annually
FREQUENCY_INDICATOR times | times a | times an | both times
PER_INDICATOR per | / | FREQUENCY_INDICATOR
PER_SECOND PER_INDICATOR RANGE SECOND /second, times a second
PER_MINUTE PER_INDICATOR RANGE MINUTE per minute, /minute
PER_HOUR PER_INDICATOR RANGE HOUR | hourly per hour, times an hour
PER_DAY PER_INDICATOR RANGE DAY | daily | nightly / day, per day
PER_WEEK PER_INDICATOR RANGE WEEK | weekly, bi-weekly | biweekly per week, /week
PER_MONTH PER_INDICATOR RANGE MONTH | monthly | bi-monthly | bimonthly /month, times a month
PER_YEAR PER_INDICATOR RANGE YEAR | yearly | annually per year, /year
PER_DECADE PER_INDICATOR RANGE DECADE times a year, per year
PER_TIMEINDICATOR PER_SECOND |
PER_MINUTE |
PER_HOUR |
PER_DAY |
PER_WEEK |
PER_MONTH |
PER_YEAR |
PER_DECADE
per min, per hour, /min, /hour
PER_DURATION_INDICATOR PER_INDICATOR RANGE DURATION_INDICATOR per day, per week, /week, /month
AMOUNT_PER_TIME_INDICATOR AMOUNT RANGE PER_TIME_INDICATOR 5 per min, per hour, 24 mg /min
AMOUNT_FREQUENCY AMOUNT RANGE FREQUENCY_INDICATOR 5 times
AMOUNT_FREQUENCY_DURATION AMOUNT_FREQUENCY RANGE DURATION_INDICATOR 5 times a day
FREQUENCY_DURATION FREQUENCY_INDICATOR RANGE DURATION_INDICATOR times a day
FREQUENCY_TIME FREQUENCY_INDICATOR RANGE TIME_INDICATOR times a hour
PERIOD_FREQUENCY_DURATION PERIOD_DETERMINER RANGE FREQUENCY_INDICATOR several times a day
PERIOD_FREQUENCY_TIME PERIOD_DETERMINER RANGE FREQUENCY_TIME several times a day
AMOUNT_FREQUENCY_TIME AMOUNT RANGE FREQUENCY_TIME several times a day
AMOUNT_PER_TIME AMOUNT RANGE PER_TIME_INDICATOR 5 per min, per hour, 24 mg /min
AMOUNT_PER_DURATION AMOUNT RANGE FREQUENCY_TIME 5 per day, 10 per week
FREQUENCY PER_TIME_INDICATOR |
PER_DURATION_INDICATOR |
AMOUNT_FREQUENCY_DURATION |
PERIOD_FREQUENCY_DURATION |
PERIOD_FREQUENCY_TIME |
AMOUNT_FREQUENCY_TIME |
AMOUNT_PER_TIME |
AMOUNT_PER_DURATION
|
FREQUENCY_ITEM

 

DOSAGE
CUBIC_CENTIMETER cc | ccs | cubic c | cubic cs | cubic centimeter | cubic centimeters | cubic centimetres | cubic centimetre | cubic centi-meter | cubic centi-meters | cubic centi-metre | cubic centi-metres
BAG bag | bags
POUND lb | lbs | pound | pounds
GRAM g | gs | gm | gms | gram | grams
MILLIGRAM mg | mgs | milligram | milligrams | milli-gram | milli-grams
MICROGRAM ug | ugs | mcg | mcgs | microgram | micrograms | micro-gram | micro-grams
KILOGRAM kg | kgs | kilogram | kilograms | kilo-gram | kilo-grams
LITER litre | litres | liter | liters
MILLILITER ml | mls | millilitre | millilitres | milliliter | milliliters | milli-litre | milli-litres | milli-liter | milli-liters
MICROLITER mcl | mcls | microlitre | microlitres | microliter | microliters | micro-litre | micro-litres | micro-liter | micro-liters
OUNCE oz | ozs | ounce | ounces
TABLET tablet | tablets | tab | tabs
UNIT CUBIC_CENTIMETER |
BAG |
POUND |
GRAM |
MILLIGRAM |
MICROGRAM |
KILOGRAM |
LITER |
MILLILITER |
MICROLITER |
OUNCE |
TABLET
NUMERIC_AMOUNT_UNIT NUMBER_AMOUNT |
UNIT
1-5 grams, 2 mcg
WORDED_NUMERIC_AMOUNT_UNIT WORD_AMOUNT |
UNIT
hundred milligrams, one ecstasy tablet
DOSAGE NUMERIC_AMOUNT_UNIT |
WORDED_NUMERIC_AMOUNT_UNIT

 

Lexicon Nonterminals
PRONOUN
DEMONSTRATIVE_PRONOUN this | that | these | those
PERSONAL_PRONOUN i | me | you | she | her | he | him | it | we | us | they | them
POSSESSIVE_PRONOUN my | our | ours | your | yours | his | her | hers | its | their | theirs | mine
REFLEXIVE_PRONOUN myself | ourselves | yourself | yourselves | himself | herself | itself | themselves
RELATIVE_PRONOUN that | which | who | whom | whose | whichever | whoever | whomever
INDEFINITE_PRONOUN anybody | anyone | anything | each | either | everybody | everyone | everything | neither | nobody | no one | nothing | one | somebody | someone | something | both | few | many | several | all | any | most | none | some
INTERROGATIVE_PRONOUN what | who | which | whom | whose

 

INTENSITY
LOW low | very low | lower | lower than | lowest | small | very small | smaller | smaller than | smallest | less | less than | less is more | least
AVERAGE average | ideal
HIGH high | very high | higher | highest | large | very large | larger | largest | more | most | excess | excessive

 

EMOTION
AFFECTION adoration | affection | love | fondness | liking | attraction | caring | tenderness | compassion | sentimentality | lovin | loving
LUST arousal | desire | lust | lusting | passion | infatuation
LONGING longing
CHEERFULNESS amused | amusement | bliss | blithe | cheerful | cheerfulness | gay | gaiety | glee | gleeful | glad | gladness | jolly | jolliness | jovial | joviality | joy | joyful | delight | delightful | enjoyed | enjoyment |happy | happiness |jubilation | elated | elation | ecstasy | euphoria | satisfaction
ZEST enthusiasm | zeal | zest |excited | exciting | excitement | thrill | thrilling | exhilaration |
CONTENTMENT contented | contentedness | Contentment | pleasure | satisfied | satisfaction | gratified | gratification
PRIDE pride | proud | prideful | pridefulness | triumph
OPTIMISM eagerness | expecting | hope | hopeful | hoping | hopefulness | optimistic | optimism
ENTHRALLMENT enthrallment | enthrall | rapture
RELIEF relief | ease | relaxation | alleviation
SURPRISE amazement | amazed | surprise | surprised | surprising | astonished | astonishment | astounded | unexpected
IRRITATION aggravation |irritation | irritated | irritating | agitation | annoyed | annoyance |disturbing | grouchiness | grumpiness
EXASPERATION exasperation | frustration
RAGE anger | rage | outrage | fury | wrath | hostility | ferocity | bitterness | hate | loathing | scorn | spite | vengefulness | dislike | resentment | vengeance
DISGUST disgust | revulsion | contempt | disgusting | disgusted
ENVY envy | jealousy | jealous | envying
TORMENT torment | tormented
SUFFERING aggravation | irritation | irritated | irritating | agitation | annoyed | annoyance | disturbing | grouchiness | grumpiness | suffer
DEPRESSION depressed | depression | depressing | cheerless | despair | despairing | dejected | hopelessness | heartbroken | brokenhearted | heartbreak | heartache | gloom | glumness |sad | sadness | unhappy | unhappiness | grief | sorrow | woe | misery | melancholy
DISAPPOINTMENT dismay | disappointment | disappointed | disappointing | displeasure | letdown
SHAME ashamed | shame | regret | regretful | regretting | remorseful | guilt | remorse | guilty
NEGLECT alienation | isolation | neglect | loneliness | rejection | homesickness | defeat | dejection | insecurity | embarrassment | humiliation | insult
SYMPATHY pity | sympathy | compassion | compassionate | sympathizing | sympathetic
HORROR alarm | shock | hysteria | mortification | fear | fright | horror | terror | scare | panic | scared | frightened | fearful | panicking | panicked | panicky
CONFUSE confused | confusing | confusion | confuse
DISCONTENTMENT discontent | discontented | unsatisfied | disgruntled | displeased | dissatisfied
EMBARRASSMENT embarrassment | embarrass | embarrassed | embarrassing | abashment | awkwardness | abashed
FORGIVENESS forgiveness | forgive | pardon | forgiving
THANKFULNESS thankfulness | thankful | appreciation | gratitude | gratefulness | appreciative | grateful
BLAME blame | blamed | blaming
NERVOUSNESS anxiety | nervousness | tenseness | tension | uneasiness | worry | anxious | nervous | tense | uneasy | worried | worrying
LOVE AFFECTION | LUST | LONGING
JOY CHEERFULNESS | ZEST | CONTENTMENT | PRIDE | OPTIMISM | ENTHRALLMENT | RELIEF
ANGER IRRITATION | EXASPERATION | RAGE | DISGUST | ENVY | TORMENT
SADNESS SUFFERING | DEPRESSION | DISAPPOINTMENT | SHAME | NEGLECT | SYMPATHY
FEAR HORROR | NERVOUSNESS

 

SENTIMENT
POSITIVE Im glad | I'm glad | Luckily | awesome | benefit | best choices | best for me | best | didnt feel sick | didn't feel sick | easier | effective | efficacy | emotions come back | favorite | feelings of happiness | get me through | good | great | handy | help A LOT | help immensely | help you | helped me out | helpin more | helping | helps | highly respectable | incredible | isnt a waste | i'snt a waste | it potentiates | most certainly help | normal | pleasant | pretty | prevents any problems | ready | relieved | safety | should be happy | stopped the W/D | to get ok | worked for me | worked perfectly | working | works | works pretty well | would help
NEGATIVE Big fucking mistake | threw up | It was bad | Its really rough | It' s really rough | NEVER work | No longer | SEVERELY dangerous | a number on | avoid using it | bad thing | bad | cant stop sneezing | could be toxic | dangerous | didnt do shit | didn't do shit | didnt go | didn't go | dirty whore | disappointed | dizzy | dont work | fall | feel sick | feel weird | freaking out | fucked up | fucking awful | fucking ever | hard | harm | hated | horrible side effects | horrible withdrawal | hurt | ineffectiveness | it sounds dreadful | lazy | miserable | nauseous | negative | neurotoxicity | no free lunch | no goer | no reduction | not sure | not worth | potential dangers | pretty shitty | prolongs the inevitable | rough | scary | shit | sketchy | still dependent | tremor | turn out bad | very wary | vomiting hard core | want to puke | weird pressure | weird | will not work | wont work | won't work | worst heartburn | worst migraine | worth a shit | wrong

 

Lexico-ontology Nonterminals

Knowledge-Aware-Search-lexico-ontology

Template Pattern Productions

Knowledge-Aware-Search-Productions

Document Annotation

AQL

Knowledge-Aware-Search-AQL

Query Matcher

Demo & Live Web Application

PLEASE SELECT A RESOLUTION >720p TO WATCH THIS VIDEO
Knowledge Aware Search Live Demo

Evaluation

Knowledge-Aware-Search-Evaluation

Funding

This project is sponsored by the National Institutes of Health (NIH) Grant No. R21 DA030571-01A1 awarded to the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) and the Center for Treatment, Interventions and Addictions Research (CITAR) titled “A Study of Social Web Data on Buprenorphine Abuse using Semantic Web Technology.” Any opinions, findings, conclusions or recommendations expressed in this material are those of the investigator(s) and do not necessarily reflect the views of the National Institutes of Health.

Contact: Delroy Cameron