Crowdly

Build frequent subword units for tokenization

✅

Detect DDoS traffic from logs

Create only relational database indexes

Partition a graph into communities

Difference between stemming and lemmatization:

They are identical

Only used in JavaScript

Lemmatization removes stop words

Lemmatization is context-aware

✅

Stemming is always better

Tokenization in NLP means:

Splitting text into words, subwords, characters, or other analyzable units

✅

Removing every noun and verb from a corpus

Calculating the density of a graph

Creating physical backups of a text database

Encrypting a document before storage

Why can web beacons create privacy concerns even when they do not contain malicious code?

They automatically anonymize all analytics records

They may collect visit or device signals without obvious interaction

They prevent cross-site tracking by design

50%

They necessarily execute arbitrary malware on the client

They can be combined with cookies to build detailed profiles

HIPAA protects:

Web cookies

Health data

Patient information

API keys

Server logs

Web Beacons are typically used for:

Encrypting databases

Tracking user behavior

Collecting interaction data

Compressing images

Protecting private data

Which options describe the canonical high-level directions of Web Mining rather than auxiliary preprocessing tasks?

Web Cache Mining

Web Content Mining

Web Schema Normalization

Web Usage Mining

Web Structure Mining

A crawler extracts product names, prices, and ratings from template-based pages into a table. Which Web Content Mining task is this?

Structured data extraction from pages

Sentiment classification of review text

Graph traversal over hyperlinks only

Automatic CSS optimization

Collecting product or service records in structured form

Which of these are NOT graph databases?

MySQL

TigerGraph

Amazon Neptune

MongoDB

Neo4j

Persistent cookies are especially useful when a site needs to:

Make third-party tracking legally unnecessary

Force every visit to be treated as a new anonymous session

Remember user preferences after the browser is closed

Maintain a login or personalization state over time

Compute aggregation windows in Spark Streaming