M Tech Dissertations

Permanent URI for this collectionhttp://ir.daiict.ac.in/handle/123456789/3

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    ItemOpen Access
    Automated sparql generation
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2015) Ladhar, Kanahiya Lal; Jat, P. M.
    Observing the last decade, semantic data on web is increasing exponentially with time and it has become difficult for amateur users to retrieve information. An enhancement of the existing web is semantic web where semantics is attached with the information, allowing machine and users to work in cooperation. A RDF is a standard model for data interchange on web, developed to interlink large amount of Linked data for web semantic and to extract data efficiently in less amount of time. To retrieve data from RDF database, SPARQL is used as a standard query language. To use SPARQL it is necessary to have knowledge of all Uri’s which is unique for each resource in DBpedia, but to figure out the Uri’s for all the resources in not feasible and predicate is restricted to domain and range. In this work we propose an interface which maps the keyword into URI, a major step towards the automated SPARQL generation. Our system take keyword-SPARQL as input and produces SPARQL as output which can be executed on SPARQL endpoint. Studying the structure of DBpedia, we create an interface which provides Auto suggestion technique to users to resolve the general problems caused due to DBpedia structure and commonly occurring typing errors . Concept and property mapping functions are used to map instances to concept in DBpedia and WSD is used to resolve the predicate disambiguation. The advantage of this approach is that users, who are unaware of the Schema of DBpedia and complexity of SPARQL, can retrieve information.
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    ItemOpen Access
    Query optimization of object oriented database through compilation and execution
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2014) Khandhar, Mihir; Divakaran, Srikrishnan
    Database is central to many applications like a website, app, software or any business applications to store the data in various formats which can be retrieved efficiently and conveniently as and when required by the users. For efficient performance of any database, one needs to organize data as well as process queries efficiently which are addressed in Database Optimization. A lot of optimization techniques have been proposed in the Relational Database. But, as time evolved, some of the complex applications require advanced efficient Query processing capabilities which are difficult to handle by Relational Database. This motivated the need for the Object Database which works on the Object Programming Language principle and can handle much of the complex queries in a much efficient way. In this thesis, we extend the standard optimization techniques from Relational Database to Object Oriented Database and then propose a method to execute the queries in object database. We also propose a sample database and illustrated query optimization of many representative queries in Object database through some examples.
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    Semantic web data management: data partitioning and query execution
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2012) Padiya, Trupti; Bhise, Minal
    Semantic Web database is an RDF database. Due to increased use of Semantic Web in real life applications, we can find immense growth in the use of RDF databases. As there is a tremendous increase in RDF data, efficient management of this data at a larger scale, and query performance are two major concerns. RDF data can be stored using various storage techniques. The RDF data used for this experiment is FOAF dataset which is a social network data. Here we study and evaluate query performance for various storage techniques in terms of query execution time and scalability using FOAF data set. Thesis demonstrates effect of data partitioning techniques on query performance. For our experiments, we have used Triple Store, Property Tables, vertically and horizontally partitioned data store to store FOAF data. Experiments were performed to analyze query execution time for all these data stores. Partitioning techniques have been observed to make queries 168 times faster compared to Triple Stores. Materialized views are used to improve query performance further for the queries which are seen frequently for social web data. Materialized views have shown better query performance in terms of execution time which is 8 times faster than the partitioned data.
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    ItemOpen Access
    SMS query processing for information retrieval
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2012) Shinghal, Khushboo; Majumder, Prasenjit
    SMS text messaging is one of the fast and popular communication mode on mobile phones these days. This study presents a query processing system for information retrieval system when queries are Short-message-Service (SMS). SMS contains various user improvisation and typographical errors. Proposed approach uses approximate string matching techniques and context extraction to normalize SMS queries with minimum linguistic resources. We have tested the system on FIRE 2011 SMS based FAQ retrieval corpus. Results seems encouraging
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    ItemOpen Access
    SPARQLGen: generation of SPARQL from pseudo BGP
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2012) Mandloi, Dipendra Singh; Chaudhary, Sanjay; Jat, Pokhar Mal
    SPARQL is the querying language and communication protocol for communicating with RDF data sources. SPARQL query requires knowledge of URIs of bound values in the triple patterns and ontological schema used by dataset. A person, even expert in SPARQL, nds hard to gure out URIs for bound values to be used in the query. This requirement brings a gap between end user and SPARQL query formation. In this work, we aim to facilitate semantic search over web of data by converting keywords into URIs, and present SPARQLGen. SPARQLGen provides an easy way of writing SPARQL query for a given query over Web of Data (RDF data). Through appropriate interface, semantic annotations of keywords are captured. We derive a Pseudo Basic Graph Pattern which is basically similar to SPARQL BGP except that it contains keywords rather than full resource URIs. Here, we propose heuristics that discover URIs for annotated keywords and build corresponding SPARQL query. SPARQLGen takes services of falcons, a semantic search engine. The Linked Open Data plays the major role in nding aliased URIs of an entity. The nal set of results contains a list of URIs of different data sources. SPARQLGen bridges the gap between end user and SPARQL query formation. The interface allows users to write user intended keywords instead of highly syntactic SPARQL query so that he/she needs not worry about the URIs of entities while writing their queries.