ElasticSearch Research & Evidence-Based Practice 2

Question 1

A researcher needs to find documents where the abstract field contains the phrase 'machine learning' within 3 words of 'classification'. Which query type is most appropriate?

Accepted Answer

span_near query

Answer

span_near query lets you specify a maximum distance (slop) between terms, making it ideal for proximity searches within a field.

Question 2

When building a systematic literature review pipeline with Elasticsearch, which aggregation type best identifies the most frequently cited journals in a result set?

Accepted Answer

terms aggregation

Answer

terms aggregation groups documents by a field value and counts occurrences, making it perfect for identifying top journals by frequency.

Question 3

A research team stores study metadata with a 'publication_date' field. They want to track the volume of publications per month over the past 5 years. Which aggregation should they use?

Accepted Answer

date_histogram with calendar_interval: month

Answer

date_histogram with calendar_interval: month creates fixed monthly buckets, which is ideal for tracking publication volume over time.

Question 4

A data scientist wants to score research papers higher when they match multiple evidence keywords rather than just one. Which Elasticsearch feature enables boosting relevance based on matching multiple optional terms?

Accepted Answer

should clause in bool query

Answer

The should clause in a bool query increases the relevance score for each additional matching condition without making any single condition mandatory.

Question 5

A research index stores clinical trial data. Analysts need to retrieve studies with sample sizes between 100 and 500 participants. Which query is best suited?

Accepted Answer

range query on sample_size

Answer

The range query is designed for numeric field comparisons using gte, lte, gt, and lt operators, making it ideal for filtering sample sizes.

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ElasticSearch Research & Evidence-Based Practice 2