Highlights
Assessment 2: Information Retrieval Techniques Problem Solving Task
Learning Outcomes This assessment assesses the following Unit Learning Outcomes (ULO) and related Graduate Learning Outcomes (GLO):
Unit Learning Outcome (ULO)
ULO 5: Demonstrate data retrieval skills in the context of a data processing system.
Graduate Learning Outcome (GLO)
GLO 1: Discipline-specific knowledge and capabilities
Purpose
This task evaluates the student's technical skills in the management of unstructured data, with potential usage in real applications. This assessment supports student understandings of the techniques related to unstructured data management and data processing
Instructions and Submission Guide
This is an individual assessment task. Students are required to submit ONE written report.
• Read these instructions and the following questions.
• ONE written report with the file name as using student ID_givenname_A2.pdf, e.g., 123456_Kevin_A2.pdf
• The report must be submitted via CloudDeakin assessment portal. The wrong submission venue or the wrong submitted file may lead to the penalty.
Question 1:
Suppose you have joined in a search engine development team to design a search algorithm based on both the Vector model and the Boolean model.
You have collected the following documents (unstructured) and plan to apply an index technique to convert them into an inverted index.
Doc 1 - data science is field to use scientific method, process, algorithm, system to extract knowledge.
Doc 2 - data mining is the process to discover pattern in large data to involve method at the database system.
Doc 3 - information system is the study of network of hardware and software that people use to process data.
To answer the below questions, you have to provide the detailed procedures step by step. You need to remove all stop words and punctuation before the process of creating the inverted index. After that, please complete the following steps:
Question 1.1:
Create a merged inverted list including the within-document frequencies for each term.
Question 1.2:
Use the index created in Question 1.1 to create a dictionary and the related posting file.
Question 1.3:
Please design three Boolean queries, (for example, web AND search) and list the relevant documents for each query. It requires the used query keyword appears in at least two documents.
Question 1.4:
Please use the Vector model to query on the inverted index, and compare the result with the Boolean model. (Hint: you can use cosine similarity and set a similarity threshold).
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