This search procedure is a reliable, lightning-fast mechanism that determines whether an exact word exists within a document.
What is Full-Text Search?
Full-text search is a search method. It involves the system scanning the entire text body (the so-called full text) of a document for the exact words in the search query.
It is one of the oldest and fastest search methods. Unlike semantic procedures, it is not about meaning, but about word-based matching (keyword matching). This functions similarly to a strict, digital index.
How Does Full-Text Search Work?
Full-text search is based on a single, ingenious principle: The system never searches the original document in real-time. Instead, it accesses a pre-built and highly optimized index.
Full-Text Search Illustrated: Index & Document
The key to speed is the so-called Inverted Index. Instead of searching every document individually (which would take a long time), the system preemptively creates a kind of global subject register across all documents.
| Traditional Register (Book) | Inverted Index (Full-Text Search) |
| Chapter 5: Search Technology | Search Technology: Document A, Document B, Document C |
| Chapter 18: Document Management | Document Management: Document A, Document D, Document E |
Index and Full-Text Search
When a search query is submitted, the system only looks up the index. It immediately finds the Document IDs that contain the word and returns them in milliseconds. The speed of this search method is thus directly proportional to the efficiency of this index. Without this index, searching would turn into a test of patience. More about the indexing process can be read in the linked glossary article.
What are the Benefits of this Search?
The utility of full-text search in the corporate context is elementary. It forms the basis for fast and reliable search results:
- Speed: Results are delivered in milliseconds. This significantly increases productivity in document management.
- Foundation for Compliance: This search method enables seamless and audit-proof searching for terms in all archived documents, which is essential for audits.
- Low System Requirements: Compared to AI-supported searches, the computing effort for pure this search is low.
What Can’t Full-Text Search Do?
The great strength of the Inverted Index (speed) is simultaneously the decisive weakness of full-text search: it is rigid and context-blind.
- Ignorance of Synonyms: If someone searches for “Contract”, but the document only contains “Agreement”, relevant results remain hidden. The system does not recognize the conceptual relationship.
- Lack of Relation: The search cannot recognize that terms like “Contract” or “Termination” all belong to the “Legal Transaction” entity.
- No Intent Recognition: This search methos does not know whether the user wants to buy something or know something. It only delivers the exact match.
How Does Full-Text Search Help in Daily Work?
In the daily corporate routine, pure full-text search is supplemented today by extended functions to enhance user convenience:
- Stemming (Word Root Recognition): The system automatically reduces words to their word root (stem) and uses this to build the index. A search for “run” thus also finds “running” and “ran.”
- Wildcard Search: The user can set placeholders (e.g.,
*). A search forClient*thus finds all terms such as “Client file,” “Client base,” or “Client relationship.”
In the daily search process, special operators (wildcards) help compensate for uncertainties in spelling or capture multiple variants of a term at once.
Extended Search Operators (Wildcards)
| Operator | Meaning | Function | Example |
Asterisk (*) | Multi-Character Placeholder | Replaces zero or more characters. | Client* finds: Client file, Clients |
Question Mark (?) | Single-Character Placeholder | Replaces exactly one character. | M?yer finds: Mayer, Meyer |
Tilde (~) | Fuzzy Search (Similarity) | Finds similarly spelled words (typos). | Appel~ finds: Apple, Appeal |
Conclusion & Outlook
Modern Enterprise Search solutions use full-text search as an indispensable foundation for speed and reliability. However, its shortcomings regarding context and fault tolerance are overcome by more complex procedures like Phonetic Search (for correct names) and Semantic Search (for meaningful connections)
