The current abundance of electronic documents requires automatic techniques that support the users in understanding their content and extracting useful information. To this aim, improving the retrieval performance must necessarily go beyond simple lexical interpretation ofthe user queries, and pass through an understanding of their semantic content and aims. It goes without saying that any digital library wouldtake enormous advantage from the availability of effective Information Retrieval techniques to provide to their users. This paper proposes an approach to Information Retrieval based on a correspondence of the domain of discourse between the query and the documents in the repository. Such an association is based on standard general-purpose linguistic resources (WordNet and WordNet Domains) and on a novel similarity assessmenttechnique. Although the work is at a preliminary stage, interesting initial results suggest to go on extending and improving the approach.

1. Università degli studi di Bari “Aldo Moro”
Dipartimento di Informatica
A Domain Based Approach
to Information Retrieval in Digital Libraries
F. Rotella, S. Ferilli, F. Leuzzi
L.A.C.A.M. ferilli@di.uniba.it, {fabio.leuzzi, rotella.fulvio}@gmail.com
http://lacam.di.uniba.it:8000
8th Italian Research Conference on Digital Libraries
Bari, Italy, February 9-10, 2012

2. Overview
● Introduction & Objectives
● Keyword Extraction
● Word Sense Disambiguation
● Synset Clustering
● A Multistrategy Similarity Measure
● Document Partitioning
● User Query Processing
● A Preliminary Evaluation
● Conclusions & Future Works
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 2

3. Introduction
Some repositories leave the responsibility of quality to the authors.
+
Anybody can produce and distribute documents.
=
Possible low average quality of the repository contents.
Users are often overwhelmed by documents that only apparently are
suitable for satisfying their information needs.
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 3

4. Introduction
● Possible way out: Information Retrieval systems
● Numerical/statistical manipulation of (key)words has
been widely explored in the literature
● Still unable to fully solve the problem
● Achieving better retrieval performance requires to go
beyond simple lexical interpretation of the user
queries
● Pass through an understanding of their semantic
content and aims
● Ontological taxonomy
● WordNet
● WordNet Domains
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 4

5. Objectives
Improving fruition of a DL
● Use of advanced techniques for document retrieval
● Try to overcome the ambiguity of natural language
● Inspired by the typical behavior of humans:
● take into account the possible meanings of words
● select the most appropriate one according to the
context of the discourse
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 5

6. Keyword Extraction
● Each document in the digital library is progressively split into paragraphs,
sentences, and single words
● Integrated in the DOMINUS framework
● Obtained the syntactic structure of sentences, and the lemmas
● Integrated in the Stanford Parser
● Classical VSM
● TF*IDF weighting
● Two filters:
● Only nouns considered
● The representation of adverbs, verbs and adjectives in WordNet is
different
● Only the top 10% keywords for each document
● To be noise-tolerant
● To limit the possibility of including non-discriminative and very general
words in the representation of a document
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 6

7. Word Sense Disambiguation
Domain Driven
One Domain per Discourse assumption: many uses of a word
in a coherent portion of text tend to share the same domain.
Prevalent domain
Prevalent domain
individuation
individuation
Extraction of all
Extraction of all
synsets for each term
synsets for each term
Extraction of all
Extraction of all
domains for each synset
domains for each synset
Choice of prevalent
Choice of prevalent
domain synset
domain synset
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 7

8. Synset Clustering
Pairwise complete link agglomerative strategy
● Each synset generates a singleton cluster
● For each pair of clusters
● If the complete link property holds
● Merge the involved clusters
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 8

9. A Multistrategy
Similarity Measure
3 components are summed and
normalized, in ]0,1[
● depth (ancestors)
● breadth (direct neighbors)
● breadth (inverse neighbors)
WordNet relationship are considered
Cooperating Techniques for Extracting Conceptual Taxonomies from Text - S. Ferilli, F. Leuzzi, F. Rotella 9

10. A Multistrategy Similarity Measure
Cosidered Relationship
member meronimy: the latter synset is a member meronym of the former;
substance meronimy: the latter synset is a substance meronym of the former;
part meronimy: the latter synset is a part meronym of the former;
similarity: the latter synset is similar in meaning to the former;
antonym: specifies antonymous word;
attribute: defines the attribute relation between noun and adjective synset
pairs in which the adjective is a value of the noun;
additional information: additional information about the first word can be
obtained by seeing the second word;
part of speech based: specifies two different relations based on the parts of
speech involved;
participle: the adjective first word is a participle of the verb second word;
hyperonymy: the latter synset is a hypernym of the former.
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 10

11. Document Partitioning
● SynsetWord structure:
● Original word
● TF*IDF weight
● Synset
● The Pairwise Clustering step returned a set of synset clusters
● For each document in the collection
● Each of its SynsetWord votes with its TF*IDF weight
● The first three clusters are chosen from the ranked list
● They represent the intensional description of the document
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 11

12. Users Query Elaboration
Overview
● Same grammatical preprocessing as in the previous phase
● Query usually very short
● No keyword extraction: all nouns retained for the next
operations
● WSD Domain Driven unreliable
● For each word, all corresponding synsets in WordNet are kept
● A single lexical query yields many semantic queries
●
All possible combinations of synsets
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 12

13. Users Query Elaboration
A Brute Force WSD
For each combination:
● a similarity evaluated against each cluster that has at
least one associated document
● using the same similarity function as for clustering
Twofold objective:
● finding the combination of synsets that represents the
best word sense disambiguation
● obtaining the most similar cluster to the involved words
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 13

14. Users Query Elaboration
Query Results
The best combination is used to obtain the list of clusters
ranked by descending relevance, that can be used as an
answer to the user search.
The results are then displayed to the user, in particular are
displayed the first n sets of document such that n is the
minimum value that shows at least 10 results.
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 14

15. A Preliminary Evaluation
The Quality of Clusters
86 documents, 4 topics:
27 general science and physics; 21 music; 15 politics; 23 religion.
Query: Reincarnation and eternal life
Best combination:
● synset: 106191212; lemmas: reincarnation; gloss: the Hindu or Buddhist doctrine that a
person may be reborn successively into one of five classes of living beings (god or human or
animal or hungry ghost or denizen of Hell) depending on the person’s own actions;
● synset: 100006269; lemmas: life; gloss: living things collectively.
Most similar cluster:
● synset: 106191212; lemmas: reincarnation; gloss: the Hindu or Buddhist doctrine that a
person may be reborn successively into one of five classes of living beings (god or human or
animal or hungry ghost or denizen of Hell) depending on the person’s own actions;
● synset: 105943300; lemmas: doctrine, philosophical system, philosophy and school of
thought; gloss: a belief (or system of beliefs) accepted as authoritative by some group or
school;
● synset: 105941423; lemmas: belief; gloss: any cognitive content held as true.
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 15

16. A Preliminary Evaluation
The Quality of Clusters
Query: Ornaments and melodies
Best combination:
● synset: 103169390; lemmas: decoration, ornament and ornamentation; gloss: something used to
beautify;
● synset: 107028373; lemmas: air, line, melodic line, melodic phrase, melody, strain and tune; gloss: a
succession of notes forming a distinctive sequence.
Most similar cluster:
● synset: 107025900; lemmas: classical, classical music and serious music; gloss: traditional genre of
music conforming to an established form and appealing to critical interest and developed musical
taste;
● synset: 107033753; lemmas: mass; gloss: a musical setting for a Mass;
● synset: 107026352; lemmas: opera; gloss: a drama set to music, consists of singing with orchestral
accompaniment and an orchestral overture and interludes;
● synset: 107071942; lemmas: genre, music genre, musical genre and musical style; gloss: an
expressive style of music;
● synset: 107064715; lemmas: rock, rock ’n’ roll, rock and roll, rock music, rock’n’roll and rock-and-
roll; gloss: a genre of popular music originating in the 1950s, a blend of black rhythm-and-blues with
white country-and-western.
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 16

17. A Preliminary Evaluation
Synthesis of Outcomes
# Query Outcomes Precision Recall
[1 to 9] music
1 Ornaments and melodies [10 to 11] religion 0.82 (1.0) 0.43 (9/21)
[1 to 9] religion
2 Reincarnation and eternal life [10] science 0.9 (1.0) 0.39 (9/23)
[1 to 4] music
3 Traditions and folks [5 to 6] religion 0.8 (1.0) 0.38 (8/21)
[7 to 10] music
[1 to 2] science
[3] politics
4 Limits of theory of relativity [4 to 5] religion 0.8 0.44 (12/27)
[6 to 15] science
[1 to 3] politics
[4] science
[5 to 6] religion
5 Capitalism vs communism [7 to 11] politics 0.61 (0.77) 0.53 (8/15)
[12] science
[13] music
[1] politics
[2] music
6 Markets and new economy [3] science 0.6 (0.7) 0.4 (6/15)
[4 to 8] politics
[9 to 10] religion
[1 to 3] politics
[4] science
7 Relationship between democracy and parliament [5 to 6] politics 0.5 (0.6) 0.33 (5/15)
[7 to 10] religion
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 17

18. Conclusions
Proposed an approach to extract information from digital libraries
● Go beyond simple lexical matching, toward the semantic content
underlying queries
The approach consists of:
● An off-line preprocessing on the entire corpus
● Find sets of synset as intensional descriptions for the documents
● An on-line phase on the queries
● Find the most suitable sense, evaluating all possible combinations
of synset against each intensional descriptions of the documents
● In order to propose as result the most relevant ones
Preliminary experiments show that this approach can be viable.
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 18

19. Future Works
● Substitution of the ODD assumption with a more elaborated
strategy for WSD
● Avoiding the pre-processing step
● To handle cases when new documents are progressively
included in the collection
● Including adverbs, verbs and adjectives
● To improve the quality of the semantic representatives of the
documents
● To explore other approaches to choose better intensional
descriptions of each document
A Domain Based Approach to Information Retrieval in Digital Libraries - F. Rotella, S. Ferilli, F. Leuzzi 19