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Prokopis Prokopidis, 2016-12-06 12:51 PM
Topic Definitions¶
A topic definition in the context of ILSP-FC is a list of terms that "define" a topic. This list is provided at runtime in a text file where each line contains a term with the following fields:
- weight (an integer, see below) for the term
- a
:
separator - a (multi-word) term to be searched in a web document fetched by the crawler (in its main, non-boilerplate content, but also in its title and keywords)
- a
=
separator - a string for one or more topics that the term corresponds to, separated by ";"
If the targetted languages are more than 1, i.e. if you run a multilingual crawl, the following fields are also needed
- a ">" separator
- a 2-digit iso language code for the language of the term
This list is an external resource that must be created before running the crawl.
One way to create it is to search for an already available term list (in, for example, the Eurovoc multilingual thesaurus) and manually modify it according to the format above. One issue with this approach is that appropriate weights should be manually assigned to each term. A simple heuristic is to assign the same weight (e.g. 100) to each term and assign lower weights to terms that may be ambiguous, i.e. terms that may correspond to multiple topics.
Here's an extract from a definition for the environment topic that can be used for a Greek monolingual crawl.
70:"πράσινο" σήμα=περιβάλλον 70:άγρια ζώα=περιβάλλον 100:άγρια φυτά και ζώα=περιβάλλον 70:άγριο θηλαστικό=περιβάλλον 50:αγροτική καταστροφή=περιβάλλον 50:άδεια για κυνήγι=περιβάλλον 50:άδεια θήρας=περιβάλλον 50:άδεια κυνηγίου=περιβάλλον 50:άδεια μπαταρία=περιβάλλον 100:άδεια ρύπανσης=περιβάλλον 25:αειφόρος ανάπτυξη=περιβάλλον 25:αέρια εξάτμισης αυτοκινήτων=περιβάλλον 100:αέριο που προκαλεί το φαινόμενο του θερμοκηπίου=περιβάλλον 100:αέριο που φθείρει το στρώμα του όζοντος=περιβάλλον
At runtime, the crawler's classifier will be initialized with a stemmed version of this topic definition:
70 πρασιν σημ περιβάλλον ell "πράσινο" σήμα 70 αγρ ζωα περιβάλλον ell άγρια ζώα 100 αγρ φυτ ζωα περιβάλλον ell άγρια φυτά και ζώα 70 αγρι θηλαστ περιβάλλον ell άγριο θηλαστικό 50 αγροτικ καταστροφ περιβάλλον ell αγροτική καταστροφή 50 αδει θηρ περιβάλλον ell άδεια θήρας 50 αδει κυνηγ περιβάλλον ell άδεια για κυνήγι 50 αδει μπαταρ περιβάλλον ell άδεια μπαταρία 100 αδει ρυπανσ περιβάλλον ell άδεια ρύπανσης 25 αειφορ αναπτυξ περιβάλλον ell αειφόρος ανάπτυξη 25 αερ εξατμισ αυτοκινητ περιβάλλον ell αέρια εξάτμισης αυτοκινήτων 100 αερι προκαλ φαινομεν θερμοκηπ περιβάλλον ell αέριο που προκαλεί το φαινόμενο του θερμοκηπίου 100 αερι φθειρ στρωμ οζοντ περιβάλλον ell αέριο που φθείρει το στρώμα του όζοντος
The main content of each fetched web document found to be in EL, will also be stemmed and normalized. Stemmed terms will be searched for in the normalized content and a score will be calculated as in section 3.5, Text Classifier of this paper. A number of thresholds that affect the way this score is calculated can be defined in the crawl's configuration file:
<classifier>
<min_content_terms>
<value>4</value>
<description>Minimum number of terms that must exist in clean
content of each web page in order to be stored.This number
is multiplied with the median value of the terms'weights and
the result is the threshold for the absolute relevance score.</description>
</min_content_terms>
<min_unique_content_terms>
<value>4</value>
<description>Minimum unique terms that must exist in clean content</description>
</min_unique_content_terms>
<relative_relevance_threshold>
<value>0.2</value>
<description>The absolute relevance score is divided by the length
(in terms of tokens) of the clean content of a document and the
calculated relative relevance score is compared with this value</description>
</relative_relevance_threshold>
</classifier>