Definition of Semantic Digital Library:
Semantic Digital Library propose
a service-oriented architecture that explicitly includes a semantic layer which
provides primitive services to the applications built on top of the digital
library. As part of this layer, a specific component is described: the PIRATES
framework. This module assists end users to complete several tasks concerning
the retrieval of the most relevant content with
respect to a description of their information needs (a search query, a user
profile, etc.). Techniques of user modeling, adaptive personalization, and
knowledge representation are exploited to build the PIRATES services in order to
fill the gap existing between traditional and semantic digital libraries. we
are designing and developing a digital platform capable of maintaining the
semantic meaning of each digital object and its content, of maintaining its
origin and authenticity, and of retaining its interrelatedness
Introduction
of Semantic Digital Library
This layer exposes its services to the user applications
through the Enterprise Service Bus located in the Integration layer. Two main
components characterize the Semantic layer:
· PIRATES Framework, which communicates with a Knowledge Base in order to
retrieve or suggest potentially relevant information from the archives. This
framework provides primitive services to automatically classify, annotate and
recommend specific content using techniques based on natural language
processing. PIRATES is composed of three components, a Cognitive Filtering
Tools module, an Automatic Tagger, and a Knowledge Base Builder.
Meta Search Engine, which exploits the document annotations provided by
PIRATES in order to recommend similar contents with respect to those retrieved
by a traditional search engine fulfilling user queries. This module can also be
used for refining a user query which has not provided enough results (query
reformulation). The presence of the Semantic Layer is aimed at improving the
information access mechanism by empowering its environment by semantic
services.
Adding Semantics to Digital
Archives:
Tagging is a textual annotation technique based on meta-data
information (i.e., tags). A tag is a keyword users use to annotate a content,
in order to organize knowledge, describe it, correlate it with other contents,
or simply to retrieve it easily in future searches. The tagging activity may be
manual if it is provided by a human user, or automatic if is it generated by a
dedicated software. Archivists can employ tags differently because they can be
guided by different tasks. Typically, tagging is used with the explicit intent of:
1. classifying content by means of a corpus of concepts that
are familiar to the archivist (e.g., taxonomies, thesauri, or any bag of
keywords representing meaningful categories for him/her)
2. summarizing resource content by means of a short list of
keywords representing the user-generated content description
3. expressing a polarity judgment about a content by means
of proper adjectives provided as tags (e.g., “sad”, “wonderful”)
4. correlating tagged resources with people and their skills
such as the level of expertise, the reputation, or the importance of a person
mentioned in the resource content (e.g.,“guru”, “geek”, “vip”, “bill-gates”,
etc.)
5. creating dichotomous classification criteria in order to
describe resources as belonging or not belonging to a particular category
(e.g., “clinical”/“not-clinical”, “statistical”/“not-statistical’,
“accepted”/“rejected”, and so on)
6. providing temporal information to a resource, for example
annotating the date of an event related to that resource.
To some extent, all these forms of tagging express a
classification intent targeted to establish effective schemata for organizing the
knowledge and facilitating content retrieval. Tagging allows users to determine
suitable labels for their resources freely without relying on any predetermined vocabulary or
hierarchy . Moreover, tags can be very effective for serendipitous browsing of
a digital archive of documents (or bookmarks) in order to find relevant
information.
Hence people tag the content with their own vocabulary and
ultimately their mental models in
order to facilitate the process of recall. Besides with these
potential benefits, manual tags suffer with some of notable limitations.
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