1. A method for event matching by analysis of text characteristics, the method comprising: acquiring a document collection comprising a plurality of documents; identifying one or more document subsets of the document collection, each comprising one or more documents, based on one or more structured metadata fields of the documents comprising one or more structured content fields such that two or more documents describing an identical event are grouped in a same document subset, wherein the one or more structured content fields comprise one or more structured content fields for an airplane model, time, location, and one or more entities associated with the event; determining whether a document in a particular document subset of the one or more document subsets is excluded from combination with other documents in the particular document subset based on the one or more structured metadata fields; after determining that the document in the particular document subset is excluded from combination with other documents in the particular document subset, determining to avoid extracting text features from the document; otherwise, extracting one or more salient text features from documents in the particular document subset by at least: extracting a particular multi-word text feature based on determining that a sequence of words of the particular multi-word text feature occurs relatively frequently given occurrence of individual words in the sequence of words of the particular multi-word text feature, wherein the particular multi-word text feature comprises an aircraft event associated with one of aircraft takeoff, aircraft landing, corrective action, aircraft speed, weather, crew observations, or aircraft subsystem; determining one or more normalized text features of an aircraft event by at least: converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using one or more regular expressions, and converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using numerical distance and normalizing alphanumeric patterns including numbers and units of measure; generating an event similarity score for pairs of documents in at least the particular document subset by comparing the one or more normalized text features extracted from the documents in the particular document subset, wherein the event similarity score comprises a weighting of the one or more normalized text features for each pair of the pairs of documents based on a rarity measure measuring word rarity; and generating a common event document list comprising sets of documents in the document collection whose event similarity scores with each other are above a similarity threshold for each pair of documents.
1. A method for event matching by analysis of text characteristics, the method comprising: acquiring a document collection comprising a plurality of documents; identifying one or more document subsets of the document collection, each comprising one or more documents, based on one or more structured metadata fields of the documents comprising one or more structured content fields such that two or more documents describing an identical event are grouped in a same document subset, wherein the one or more structured content fields comprise one or more structured content fields for an airplane model, time, location, and one or more entities associated with the event; determining whether a document in a particular document subset of the one or more document subsets is excluded from combination with other documents in the particular document subset based on the one or more structured metadata fields; after determining that the document in the particular document subset is excluded from combination with other documents in the particular document subset, determining to avoid extracting text features from the document; otherwise, extracting one or more salient text features from documents in the particular document subset by at least: extracting a particular multi-word text feature based on determining that a sequence of words of the particular multi-word text feature occurs relatively frequently given occurrence of individual words in the sequence of words of the particular multi-word text feature, wherein the particular multi-word text feature comprises an aircraft event associated with one of aircraft takeoff, aircraft landing, corrective action, aircraft speed, weather, crew observations, or aircraft subsystem; determining one or more normalized text features of an aircraft event by at least: converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using one or more regular expressions, and converting one or more variations of at least one salient text feature of the one or more salient text features to a standard form using numerical distance and normalizing alphanumeric patterns including numbers and units of measure; generating an event similarity score for pairs of documents in at least the particular document subset by comparing the one or more normalized text features extracted from the documents in the particular document subset, wherein the event similarity score comprises a weighting of the one or more normalized text features for each pair of the pairs of documents based on a rarity measure measuring word rarity; and generating a common event document list comprising sets of documents in the document collection whose event similarity scores with each other are above a similarity threshold for each pair of documents. 7. The method of claim 1 , further comprising presenting the common event document list, matching text features, non-matching text features, or a combination thereof.