Presentation is loading. Please wait.

Presentation is loading. Please wait.

IDS 1 Extended Keyword Index & Improved Search for Semantic e-Catalog 이동주.

Similar presentations


Presentation on theme: "IDS 1 Extended Keyword Index & Improved Search for Semantic e-Catalog 이동주."— Presentation transcript:

1 IDS 1 Extended Keyword Index & Improved Search for Semantic e-Catalog 이동주

2 IDS2 Contents  Motivation  Semantic e-Catalog  Search In e-Catalog  Search Strategy  Keyword Index  Scoring Fucntion  CatOnt  Conclusion & Future Work

3 IDS3 Motivation  Keyword Search e-Catalog take a very important role in e-Business many people want to search product information using simple keyword  Semantic e-Catalog legacy e-Catalog couldn’t fully express the various and complex product information and relationship semantic e-Catalog system needs suitable search strategy needs

4 IDS4 Semantic e-Catalog (1) Product Data Attribute P2 v P4 v P3 v P4 v P1 v … …… Classification Scheme2 …… Classification Scheme3 …… Classification Scheme1 ……

5 IDS5 Semantic e-Catalog (2) EC = {E, R}, E = {P, C, A, U} ME ∈ {C, A, U}, MA = {α 1, α 2,..., α m } me = {(α, v)| α ∈ MA, v ∈ VALUE} p = { (a, v)| a ∈ A, v ∈ VALUE} R = { (e 1, e 2, r)| e 1 ∈ E 1, e 2 ∈ E 2, E 1 ∈ E, E 2 ∈ E, r ∈ DR} EC : Electronic Catalog E : Entity R : Relationship DR : Definition of Relationship ME : Meta Entity, MA : Meta Attribute P : Product, C : Classification Scheme A : Attribute, U : Unit Of Measure

6 IDS6 Search In e-Catalog Search Query e-Catalog DB Sorted List Query Analyzer DB Interface Ranker Search Engine

7 IDS7 Search Strategy  use simple keyword  use semantics implied in e-Catalog relationship between entities construct keyword index of entity’s information (values of attributes) construct extended keyword index with tagging  use semantics implied in search query extract useful keyword and tag meaning

8 IDS8 Extended Keyword Index  extended keyword (voc, tag 1, tag 2, …, tag t )  extend the definition of semantic e-Catalog with extended keyword index e = { (a, v)| a ∈ ATT, v ∈ VALUE} if e is Product ATT is A else ATT is MA ivoc = (voc, tag 1, tag 2, …, tag t ) tag1 is a’s identifier e = {ivoc 1, ivoc 2, …, ivoc v } VOC : Vocabulary

9 IDS9 RDB Structure for Semantic e-Catalog e-Catalog DB Product (ComAtt) Classification Scheme G2B Attribute UOM Attribute Group UOM Group Product (IndAtt) Classification Scheme GUNGB Classification Scheme UNSPSC VOC

10 IDS10 Extracting Keyword Indexes  different extracting mechanism according to attributes name description numeral just use original

11 IDS11 Process of Keyword Index Extraction Analyze Morpheme Structure Select possible result Extends the word using dictionaries Eliminate the useless word Count frequency and mark order Eliminate duplicated word use KLT module it’s different according to attribute Do tagging and return Keyword List

12 IDS12 Tags attrattribute identifier klt_patnword pattern klt_pos types of stem klt_pos2normal types of stem klt_josajosa klt_eomieomi domain composedindicate how ivoc was composed & extended k_idxorder of the ivoc in original v k_cnttotal num extended ivoc from original v freqfrequency of voc in original v

13 IDS13 Scoring Function from extended definition with extended keyword index e = {ivoc 1, ivoc 2, …, ivoc a } Score(Q, e) = ∑ I,j Score(q i, ivoc j ) Score(Q, e) extend the query Q = {q 1, q 2, …, q i, …, q n } q i = {voc, tag 1, tag 2, …, tag s } generalize with relationship r related e Score(Q, e) = ∑ I,j Score(q i, ivoc j ) + ∑ k,l w r k *Score(Q,e’ l ) w rk : weight of relation r k e’ l : related entity using r k Score(q i, ivoc j ), w r dominate total score

14 IDS14 CatOnt  Parser  Loader easily extensible semi-automated loading tool using XML specification  Searcher not implemented yet

15 IDS15 Loading Process Specification - Entity Converting

16 IDS16 Loading Process Specification - Relationship Converting

17 IDS17 Loading Process Specification - Keyword Index Construction (1)

18 IDS18 Loading Process Specification - Keyword Index Construction (2)

19 IDS19 Conclusion & Future Work  Conclusion propose extended keyword index using various tag for semantic e-Catalog implement semi-automated converting tool from legacy e- Catalog to semantic e-Catalog with easily extensible XML specification propose scoring function which extended keyword index is applicable  Future work contrive feasible scoring function and methods to assign weights of each relationship implement Searcher extend this motel to general E-R model


Download ppt "IDS 1 Extended Keyword Index & Improved Search for Semantic e-Catalog 이동주."

Similar presentations


Ads by Google