Text Information Management System (TIMS) MCQs With Answer
Timely access to accurate text-based data is essential in pharmacy practice and research. A Text Information Management System (TIMS) organizes, indexes, retrieves, and analyzes clinical notes, regulatory documents, scientific literature, and drug monographs to support B. Pharm students and professionals. These TIMS MCQs cover architecture, indexing methods (inverted index, metadata), text preprocessing (tokenization, stemming, stop-word removal), NLP techniques (named entity recognition, TF–IDF, semantic search), database integration, security and compliance, and real-world applications such as pharmacovigilance, literature review, and decision support. Questions emphasize practical understanding, search strategies, and quality metrics (precision, recall). ‘Now let’s test your knowledge with 30 MCQs on this topic.’
Q1. What is the primary purpose of a Text Information Management System (TIMS) in pharmacy?
- To manufacture pharmaceutical products
- To organize, index, retrieve, and analyze text-based drug and clinical information
- To monitor temperature in drug storage facilities
- To perform chemical synthesis simulations
Correct Answer: To organize, index, retrieve, and analyze text-based drug and clinical information
Q2. Which data structure is most commonly used in TIMS to enable fast full-text search?
- B-tree index
- Relational join table
- Inverted index
- Hash chain
Correct Answer: Inverted index
Q3. In TIMS, which of the following is considered metadata for a document?
- Body text of a clinical note
- Scanned image pixels
- Title, author, and publication date
- Character encoding scheme
Correct Answer: Title, author, and publication date
Q4. What does tokenization refer to in text preprocessing?
- Removing duplicate documents from a corpus
- Splitting text into meaningful units such as words or phrases
- Encrypting text for secure storage
- Mapping synonyms to a single concept
Correct Answer: Splitting text into meaningful units such as words or phrases
Q5. Why are stop-word removal and filtering important in TIMS text processing?
- They increase file sizes for better archiving
- They remove high-frequency, low-significance words to reduce noise and index size
- They translate documents into other languages
- They identify authorship of documents
Correct Answer: They remove high-frequency, low-significance words to reduce noise and index size
Q6. How does stemming differ from lemmatization?
- Stemming uses dictionaries; lemmatization trims suffixes heuristically
- Stemming trims words to base stems heuristically; lemmatization returns dictionary-based lemmas considering context
- Stemming detects entities; lemmatization tokenizes text
- Stemming encodes documents; lemmatization compresses them
Correct Answer: Stemming trims words to base stems heuristically; lemmatization returns dictionary-based lemmas considering context
Q7. What does TF–IDF measure in document scoring?
- Transaction frequency over indexed data
- Term frequency adjusted by inverse document frequency to weight discriminative terms
- Total field indexing depth factor
- Time factor for document freshness
Correct Answer: Term frequency adjusted by inverse document frequency to weight discriminative terms
Q8. Which similarity metric is commonly used with vector-space models to compare document vectors?
- Euclidean distance without normalization
- Cosine similarity
- Hamming distance
- Manhattan distance
Correct Answer: Cosine similarity
Q9. Named Entity Recognition (NER) in a TIMS for pharmacy is primarily used to identify which items?
- Operating system versions
- Drug names, dosages, adverse events, and patient identifiers
- Network traffic patterns
- File compression algorithms
Correct Answer: Drug names, dosages, adverse events, and patient identifiers
Q10. When processing scanned drug labels or handwritten prescriptions, which TIMS component is essential?
- Optical Character Recognition (OCR)
- Relational normalization
- Term frequency filtering
- Part-of-speech tagging
Correct Answer: Optical Character Recognition (OCR)
Q11. Which controlled vocabulary is commonly used to index biomedical literature relevant to pharmacy?
- DICOM
- MeSH (Medical Subject Headings)
- JPEG
- ISO 9001
Correct Answer: MeSH (Medical Subject Headings)
Q12. How can TIMS support pharmacovigilance activities?
- By manufacturing generic drugs
- By automatically detecting and aggregating mentions of adverse drug reactions from literature and reports
- By controlling HVAC systems in pharmacies
- By replacing clinical trials
Correct Answer: By automatically detecting and aggregating mentions of adverse drug reactions from literature and reports
Q13. The inverted index maps which elements to which?
- Documents to users
- Terms to lists of documents and positions where they occur
- Authors to their affiliations
- Files to server locations
Correct Answer: Terms to lists of documents and positions where they occur
Q14. In information retrieval, what is precision?
- The total number of indexed terms
- The proportion of retrieved documents that are relevant
- The proportion of relevant documents retrieved out of all relevant documents
- The time taken to return the first result
Correct Answer: The proportion of retrieved documents that are relevant
Q15. What does the F1 score represent in TIMS evaluation?
- The ratio of index size to corpus size
- The harmonic mean of precision and recall
- The sum of precision and recall
- The average document retrieval time
Correct Answer: The harmonic mean of precision and recall
Q16. Which query type allows combining terms with AND, OR, and NOT operators?
- Fuzzy search
- Boolean query
- Vector-ranked query
- Semantic embedding lookup
Correct Answer: Boolean query
Q17. Faceted search in TIMS is most useful for what purpose?
- Encrypting search results
- Filtering search results using structured metadata like year, drug class, or study type
- Automatically translating abstracts
- Generating synthetic clinical data
Correct Answer: Filtering search results using structured metadata like year, drug class, or study type
Q18. Which ranking function is widely used to compute document relevance in modern search engines and TIMS?
- BM25
- K-means clustering
- PageRank for documents only
- Levenshtein distance ranking
Correct Answer: BM25
Q19. What is concept normalization in TIMS?
- Converting all PDFs to plain text
- Mapping different surface forms and synonyms to a canonical medical concept or identifier
- Compressing documents to save space
- Translating concepts into multiple languages
Correct Answer: Mapping different surface forms and synonyms to a canonical medical concept or identifier
Q20. Which approach is typically used to group similar documents without labeled training data?
- Supervised classification
- Unsupervised clustering
- Rule-based extraction with gold labels
- Cross-validation labeling
Correct Answer: Unsupervised clustering
Q21. Supervised document classification in TIMS requires what key resource?
- A large unlabeled corpus
- Manually labeled training examples for each target category
- Only metadata fields
- Encrypted storage
Correct Answer: Manually labeled training examples for each target category
Q22. Which terminology standard focuses on normalized drug names and codes useful in TIMS integration?
- SNOMED CT
- RxNorm
- ICD-10
- DICOM
Correct Answer: RxNorm
Q23. Why is an audit trail important in TIMS for pharmacy applications?
- It speeds up searches
- It records user actions and access to support compliance and traceability
- It translates documents to plain language
- It removes duplicate documents automatically
Correct Answer: It records user actions and access to support compliance and traceability
Q24. Which security measure protects TIMS data both at rest and during transmission?
- Tokenization only for search queries
- Encryption using strong algorithms for stored data and TLS for transit
- Compression to reduce file size
- Stemming of sensitive fields
Correct Answer: Encryption using strong algorithms for stored data and TLS for transit
Q25. For integrating TIMS with external literature databases and EHRs, which interface style is commonly used?
- RESTful APIs with JSON or XML payloads
- FTP file dumps only
- Local hard-drive sharing only
- Manual export/import of paper files
Correct Answer: RESTful APIs with JSON or XML payloads
Q26. Which structured data format is commonly used in clinical document exchange standards like HL7 CDA?
- CSV only
- Binary blobs
- XML
- Plain text without tags
Correct Answer: XML
Q27. What advantage does full-text indexing provide over metadata-only indexing in TIMS?
- Lower storage requirements
- Ability to search within the body of documents for terms, phrases, and context
- Faster metadata updates
- Eliminates the need for security controls
Correct Answer: Ability to search within the body of documents for terms, phrases, and context
Q28. Record deduplication in TIMS is important because:
- It reduces the number of users
- It ensures a single canonical record per document or citation, improving result quality and analytics
- It increases data redundancy
- It obfuscates provenance
Correct Answer: It ensures a single canonical record per document or citation, improving result quality and analytics
Q29. In the TF–IDF formula, what does TF represent?
- Term frequency — how often a term appears in a document
- Token form — the canonical lemma of a word
- Time factor — document age
- Text format — encoding standard
Correct Answer: Term frequency — how often a term appears in a document
Q30. Which evaluation metric is commonly used to assess ranked retrieval effectiveness in TIMS?
- Mean Squared Error (MSE)
- Mean Average Precision (MAP)
- Confusion matrix only
- Throughput per second
Correct Answer: Mean Average Precision (MAP)

I am a Registered Pharmacist under the Pharmacy Act, 1948, and the founder of PharmacyFreak.com. I hold a Bachelor of Pharmacy degree from Rungta College of Pharmaceutical Science and Research. With a strong academic foundation and practical knowledge, I am committed to providing accurate, easy-to-understand content to support pharmacy students and professionals. My aim is to make complex pharmaceutical concepts accessible and useful for real-world application.
Mail- Sachin@pharmacyfreak.com
